Посты автора Amnon Levav

Amnon Levav

Co-Founder and C-IO (Chief Innovation Officer) at SIT

On Indicators and Measuring Innovation – Part 2

Published date: August 8, 2021 в 2:00 pm

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Category: Innovation,Organizational Innovation

In Part 1 of this micro-series we mentioned 6 observations about indicators and measurements in general, with a focus on some common difficulties. In this installment, we will look at several points relating specifically to the measurement of innovation. This is in no way intended to be a comprehensive treatment of the subject, but I will try to cover some useful points.

Let’s start with the question of the necessity and viability of measuring innovation. When we worked with Tal Givoly, at the time Chief Scientist of the Israeli software company Amdocs, he used to say: “Management is so interested in innovation, that it plants a seed and then pulls it out of the ground every day to see how its roots are growing.” I like to quote him to managers as a call to caution, not only in meddling with innovation but also on trying to monitor it too closely. Still, the opposite approach is no less misleading. According to this, innovation is a magical phenomenon, a spark that one cannot ignite at will, let alone measure, and any attempt at doing so will result in extinguishing the fire. This is obviously misguided since, without measuring the results of your innovation efforts there is a slim chance that you will receive the funding and support to sustain them beyond the initial burst of enthusiasm that started the drive.

Contrary to the “mystical” attitude, we tend to say, with only a bit of simplification, that innovation is like any other business process and therefore should be measured just as you would, say, your sales or efficiency efforts. So, assuming that innovation must be monitored and measured, there are two basic intuitions as to how this should be conducted. The first stems from the following logic: one’s motivation to be innovative is the wish to achieve the organization’s goals (see our post on the definition of innovation) and therefore these very goals, as expressed by their corresponding indicators, can adequately assess the value of our efforts to innovate. If we launch an innovation drive which does not result in an impact on our regular business indicators, then we are wasting our time and money. Therefore, the only indicators that an organization requires in order to monitor and evaluate its innovation efforts are those that are used to measure its performance anyway.

 

 

The appeal of this approach is that it both simplifies the measurement process and ties the innovation efforts inextricably to the company’s goals. Unfortunately, it has two grave shortcomings: 1) it is very hard to isolate the influence of your innovation efforts from the myriad factors that influence business results (factors both external – a pandemic, say, or internal – flaws in a product, or unwise allocation of resources); 2) even when you can isolate the contribution of your innovation activities, their influence on business goals will be evident only after several months, or even years. So how do you monitor your activities and make decisions as you go along, if their effects will appear only, say, within 6 months?

These difficulties often lead innovation leaders to adopt the opposite approach: since it is virtually impossible to isolate, especially in real time, the output of innovation efforts, it is seen as wiser to simply measure inputs. You hatch your plans for innovation, define specific activities, and closely monitor their delivery and implementation.

 

This is indeed a much more practical approach, which lends itself easily to project management and real time decision making. The only trouble is that you may find yourself beautifully and efficiently implementing a useless plan, that does not translate into any important benefit.

 

Our suggestion is, therefore, to create a dynamic “sliding scale” approach to measuring innovation activities, which I will demonstrate in the following scenario (derived, with some generalizations and simplifications, from our work with various companies and organizations).

Imagine that you have decided to train 400 of what we call “Innovation Coaches” (in a forthcoming post, we will describe the design, deployment and management of such a coach community. Click here to receive a notification when the post comes out). Their goal is to promote innovation throughout the organization through the facilitation of innovation sessions. The first indicator will therefore be: number of coaches trained. Since you had reached the conclusion that there was a need for 400 coaches, you want to make sure that they are trained as planned. Not a trivial task, given both the logistic requirements and the HR challenges.

 

But, of course, training a large and increasing number of coaches can end up being a huge waste of time and resources, unless they are delivering results, so, upon completion of the training of your first batch of, say, 16 coaches, you must immediately start measuring the next indicator: number of sessions delivered per coach. This helps assess the cumulative effect of the coaches on the organization, and along the way gives you some insight on the percentage of active coaches out of those who have undertaken the training (if less than 80% are somehow active, we recommend you review either the quality of the training or the trainees’ selection process, or both).

Obviously, as you celebrate a hopefully growing number of sessions, you may only be causing an even greater waste of people’s time and therefore your company’s resources. All depends on what they are actually achieving in their sessions, which is extremely difficult to assess, given that the impact of the participation in a session on a participant’s brain and behavior is extremely difficult to measure. You can therefore resort to a simplified proxy, the most practical and direct you can measure, which is the number of ideas produced in a session, to assess its productivity.

 

These are only the first three steps in an ongoing process. But how should this process be timed? How soon should one move from one indicator to the next? The proper answer to these questions is crucial to the success of the entire enterprise, not only of the measurement itself, but also the actual results, since the mere act of measurement exerts, as we all know, a strong influence on the measured activities. Say that a coach has graduated from her training. She is keen on trying out her new skills, but, on the other hand, she is a bit hesitant about having to stand up and lead her peers, or maybe even her superiors, through an exercise that has less than a 100% probability of success. She may also have to contend with a lack of support from her boss who is complaining that she is behind schedule in her regular work. The knowledge that someone is counting the number of sessions she runs can nudge her in the right direction, together with, perhaps, an extra carrot, such as the promise that any coach who facilitates, say, 6 sessions in the first two months is eligible for participation in an advanced training. So, counting the number of delivered sessions is probably a good idea immediately after coaches’ graduation from their training. But caution! In this fragile stage, counting the number of ideas produced in the session is nearly always premature, and most likely will significantly decrease the number of sessions and lower the percentage of active coaches! “Now, I don’t only need to add to my workload, argue with my boss, stand in front of not-always-collaborative colleagues and risk the embarrassment of wasting everyone’s time in what could turn out to be a useless session, they also want to monitor the number of ideas that came out? I’ll need to spend time documenting and reporting, and then find myself being scolded because they came to the conclusion that my session hadn’t been productive enough?”. Time and again we see that when management pushes to measure session results too early, coaches react either by lowering the number of sessions they facilitate, or by conducting them without reporting, which, in terms of organizational evaluation, amounts to the same thing. This phenomenon emphasizes two key dilemmas in measuring innovation activities:

  1. What you measure doesn’t only affect what you know but also what happens to those you are measuring;
  2. The more data you collect about an activity, and the more you tend to impose reporting efforts on the actors, the less time, energy and motivation they will have to do the actual work.

We strongly recommend, therefore, that you allow coaches to feel confident with conducting sessions, hopefully even enjoying the process, before you start monitoring the sessions’ outcomes. But, at some point, this must happen, and as you start counting the number of ideas produced per session, the next question arises. As we have all painfully learned, mainly thanks to the inefficacy of Brainstorming, quantity of ideas is not only not a guarantee of quality but can also become a burden and an energy drain. Which is why the next indicator is required: % of ideas from a session that made it into the company’s idea-development pipeline. Subsequently, you can select one or more stages of your development process and count the ideas that achieve each one or jump to the next important milestone: number of ideas launched into the market (or, if your output is not products into market, the equivalent measure such as processes changed, services offered, social programs launched, etc.).

 

Using this same logic, the sliding scale for measuring the results of your innovation efforts can be extended according to your organization’s process of product development, or project management. Common additional stages that can be added to the scale are revenues, profits, savings or market share obtained through the launch of a product or initiative, thus converging what started out in one extreme pole as a measurement of pure inputs into the opposite pole of relying on those indicators that monitor your organization’s goals and objectives.

 

Note that the approach described here attempts to address some of the pitfalls and follow some of the guidelines mentioned in my former post on the subject:

  1. Be practical by starting superficially, but do not be daunted by the difficulties and insist on going further and deeper;
  2. Consider the needs both of those who are doing the measuring and those who are being measured;
  3. Remember that measuring is an invasive process that affects the measured for good and bad, and timing can crucially determine which one it is;
  4. Consider carefully what you decide to measure, and be prepared to defend the rationale of its importance;
  5. Be transparent about the results, whatever they end up demonstrating.

In a future post, we will describe how this same approach can be expanded to apply to organizational innovation, rather than to a specific activity, by breaking up the large organizational effort into what we call The 7 Elements of Organizational Innovation. Meanwhile, we recommend that you try to apply the sliding scale approach to one or several of your innovation activities. And we would love to hear how it goes and what you learn.

How to Embrace Failure Without Falling on Your Face

Published date: August 4, 2021 в 3:30 pm

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Category: Innovation,Methodology,Strategy

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Many years ago, I presented what I considered to be a very cool project to an extremely smart VP of Marketing in a large B2C company on the East Coast of the US. Fortunately, she shared my enthusiasm, and the process of engaging us for the project was running along nicely. It was an ambitious and somewhat risky project in the sense that it required the involvement of about 20 high-level managers who were very skeptical about its chances of success. This put “my” VP in the stressful position of either ending up as the initiator of notable success or being forever remembered as the perpetrator of a huge mistake (could she embrace failure?).

At some point, she asked me: “Can we make absolutely sure this will succeed?”And, silly me, I answered with a big smile: “Of course not. Don’t you remember? One of our key messages in this project is that if you innovate you must embrace the risk of failure. So since we are designing such an innovative project, of course, there is a risk that it will fail.” Obviously, we didn’t get the project, because, regardless of the oft-quoted cliché, nobody really wants to “celebrate failures”. People want successes. And if there is one thing they will avoid at all costs, it is failure.

 

Embracing Failure, the Contradiction

 

There seems to be a contradiction: We want to think ahead. We want to try new things. We want to innovate and embrace failure as part of the inventive process. At the same time, we want to be in control of our outcomes. We cannot afford to make mistakes.

This leads to a dilemma: Companies encourage their employees to fail and learn. But they expect them not to fail.

Failures are at best unwanted – at worst systematically concealed, to avoid blame or punishment. Pressure is a means of control. The result: a fear of failure.

The prevalence of fear of failure in companies is alarming considering how paralyzing it can be for the companies’ development.

Three reasons for this troublesome effect:

1. Risk Aversion

Here is one cliché that is absolutely true: Failure is an essential part of innovation. When prototyping a new product, expect failure. That’s what prototypes are for, and that is why you will work on several consecutively, or even in parallel. Therefore, the maxim fails fast and try again.

But, if every failure is considered a mini-disaster, who wants to even consider risking it? Rather, the ultimate goal is to achieve full control of the process. Hence, any change or novel idea is treated as a potential threat.

 

2. Loser-phobia

If one strives to overcome one’s Cognitive Fixedness, a fundamental tool is the ability to reflect on one’s actions and to engage in metacognition (a reflection on one’s thinking processes). Every failure thus becomes a source of learning and a driver of change.

But, when your failures are perceived as a sign of being a “loser,” what are the chances that you will actually take the time to confront your failures, reflect on them, and draw useful conclusions?

 

3. Who? Me?

In cultures that do not truly accept failures, there is a strong incentive to underreport them and to avoid any public reference to them, let alone an open analysis.  This greatly increases, obviously, the probability that the same mistakes will be repeated. A good litmus test: Ask anyone who tells you that you should “embrace failure”, if they are willing to share a recent one of their own. Most chances are they won’t, and that tells you what you will be risking if you share yours.

You probably agree that it can be very beneficial to embrace failure in certain areas – in an honest and consistent manner. But in other areas, we cannot allow for mistakes. The point is, to make this distinction explicit and communicate it to everyone involved. Clarity is key.

 

Instead of pretending to universally embrace failure, you map out areas in which failing is acceptable. Then, you commit yourself to this map.

Here are some actions you may consider to embrace failure:

Mark your “control towers”

Imagine working in a control tower. There is obviously no way to embrace failures here. Imagine an airport with 5000 landings and take-offs per month. a mistake rate of 0.01% would imply 5 crashes per month. There are such “control towers” in every company. In some areas, even if a leader doesn’t care to admit it, failure is not an option. Being explicit about your “control towers” is crucial, if you want people to avoid these specific mistakes at all costs. Only then, everyone is on the same page: We give our best to prevent failure and if it happens, we report it. In other areas, the expectation might not be as clear. 

We suggest three mechanisms: define roles, draw lines and install safety nets.

When defining roles, you assign to a specific group of employees the role of innovators. It is then clear to everyone that this group will generate ideas, try new things – and occasionally fail. Your “innovators” will enjoy the freedom to explore and develop new ideas. At the same time, they will be accountable for their failures as part of the process.

Drawing lines means, defining which parts of a project are open to experimentation and those that are not. Within the defined lines, failure is acceptable. Innovation is welcome.

Safety nets are a similar idea, on a different level. To limit the impact of failures, you innovate in specific areas, e.g. those that are not part of your core business.

In defining roles, drawing lines and installing safety nets, we map out areas in which failures are acceptable. Only then we can truly claim: We embrace failure. Feel free to innovate.

In addition to the above actions, you can also utilize some advice from experts on the subject. 

Have a backup plan

Leon Ho says that it never hurts to have a back-up plan. The last thing you want to do is scramble for a solution when the worst has happened. “Hope for the best, prepare for the worst.” This old adage holds solid wisdom. Having a backup plan gives you more confidence to move forward and take calculated risks.

Perhaps you’ve applied for a grant to fund an initiative at work. In the worst-case scenario, if you don’t get the grant, are there other ways you could secure the funds? There are usually multiple ways to tackle a problem, so having a back-up plan is a great way to reduce anxiety about possible failure.

Leon Ho (https://www.lifehack.org/articles/lifehack/how-fear-of-failure-destroys-success.html)

Identify the consequences

Theo Tsaousides says that in order to attenuate fear of failure, first identify the consequences of failing that scare you the most and evaluate your ability to deal with these consequences. Instead of talking yourself out of the fear by hoping that nothing negative will happen, focus on building confidence to deal with the consequences.

Here are some questions to ask yourself:

  1. Which of these consequences scare you the most?
  2. How much impact will they have on you? Are they merely unpleasant or life-threatening? Will they just make you feel uncomfortable, or will they hurt you deeply and irreparably?
  3. How quickly will you move on? Are the consequences permanent or reversible? Are they short-lived, or will they linger forever?
  4. How well can you handle them? Can you exercise damage control, or will you hide and disappear?

Theo Tsaousides (https://www.psychologytoday.com/us/blog/smashing-the-brainblocks/201801/how-conquer-fear-failure)

Now that you’re equipped with the knowledge, it’s your turn: Tell us about YOUR experience in dealing with a Fear of Failure and check out one of our latest article on how to manage airtime!

On Indicators and Measuring Innovation – Part 1

Published date: August 1, 2021 в 2:00 pm

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Category: Innovation,Organizational Innovation

On June 30th, I posted about the meaning of the term “innovation”. These were the post’s opening sentences:

When I typed “definition of innovation” into Google the other day, I came up with 1,710,000,000 replies, which means absolutely nothing, of course, raising the question why the arguably most influential company on earth has been consistently feeding us with this useless piece of data for so many years. So, I promise to use this very same opening sentence in a future post (repurposing, saving on first-sentence-emissions) about some common popular fallacies around indicators and measurement.

Keeping my promise here, I reiterate my bewilderment and will attempt to use this example to shed some light on the oft-asked question: how should innovation be measured? This question came up yet again last week in a conversation with an Innovation Manager in a medium-sized financial company. “They [management] are demanding that we boost innovation throughout the company when I don’t even know what innovation is nor have any idea how to measure it.” The former question was addressed by the post mentioned above. In this post (both parts) we will address the latter.

Here, in Part 1, we will start by using the example of Google’s indicators to share some observations on what should or shouldn’t be done when measuring performance in general. In Part 2, we will analyze some specifics of measuring in the context of innovation.

As I write this, I repeat my search for “definition of innovation”. Why does Google choose to share with me that my search took 0.60 to complete and that it came up with 1,860,000,000 results? Why would I care? What can I do with these two pieces of information? One can imagine that in the late 1990’s this pair of indicators served to signal both “look how fast our engine is”, and “see how many results we can provide you with”. Even then, there was a glaring discrepancy between the search engine’s stated differentiator and the indicators communicated. Google claimed the superiority of its algorithm based on the quality of its results, not their quantity nor the speed of their delivery, so why were they boasting characteristic #1 while measuring #2 and #3?  This is the result of my repeated search today:

 

Keen readers will have noticed that the number that appears above constitutes an increase of 150,000 finds over my former search, quoted in the opening paragraph. Say that Google has indeed found 150,000 additional hits in less than a month. So what? Have I gained anything from this increase? Obviously not. Clearly, then, these indicators have not been selected to cater to my needs as seeker of information. Why were they selected then? One suspects that a possible reason is that they are simply easy to measure. So, the first observation on the misleading use of indicators is:

Observation #1: People and organizations tend to skew towards indicators that are easy to measure.

Ben Gomes, Google’s Vice-President of Engineering, has been quoted as saying, “…our goal is to get you the exact answer you’re searching for faster.” He goes on to explain: “Our research shows that if search results are slowed by even a fraction of a second, people search less (seriously: A 400ms delay leads to a 0.44 percent drop in search volume, data fans).”

Note that although the professed goal is to provide an “exact answer” there is no indicator to measure to what extent this important measure has been attained. This lacuna may be attributed either to a harsher variant of Observation #1 (above):

Observation #1*: If you haven’t figured out how to measure something, disregard it (even if you know it is crucially important).

Or, in more unfortunate cases:

Observation #2: If you’ve figured out how to measure it, but you’re not happy with the results, hide them.

For obvious reasons, we don’t expect Google to show us a search result that looks like this:

 

But wait, you may say, the Google VP did explain the huge importance of speed, so that is a crucial factor that should be measured. Yes, it may be crucial, but for them, rather than for you. This, then, is a prime example of:

Observation #3: Technologists and bureaucrats will tend to measure and communicate indicators that are important for them, rather than for their users/clients.

It is, no doubt, of the utmost importance for Google’s techies to measure and monitor the precise duration of each and every one of the 5.4 billion(!) daily searches (2020) on their awe-inspiring platform. But that does not at all mean that this specific piece of data about my search is of any interest to me. Ask yourself: Have you ever noticed this number? If I tell you that your search x took 0.36 seconds or your search y an agonizing 0.72, would these numbers mean anything to you? It is a stretch to imagine that Google, with its 135,301 employees and 182,527 billion US$ revenue (both numbers refer to Alphabet, end of 2020) can’t figure out that these two indicators are respectively useless and meaningless to their users. Why then, do they appear so prominently? Another possible explanation could be:

Observation #4: If you prefer to avoid sharing certain indicators, direct the spotlight to others.

This may be the most sensible explanation of the Google indicator puzzle: speed and quantity may actually be playing the role of what I propose to name “decoy indicators”. The function of this class of indicators is to enable a company to offer a semblance of transparency, while in fact obfuscating all those indicators that its audience could really be interested to monitor but is not even aware of. The Google-search-indicator-set of our dreams would maybe include some or all of these:

 

A majority of these indicators would probably be as useless to most of us as the two original ones, but would at least supply a welcome variation on the theme, or perhaps could be rotated throughout searches so that the user would either select those she wished to see or would be served a random selection of 2-3 each time. The other indicators could, say, be accessed by clicking on an icon. Does it really matter which indicators are selected? It could, very much.

Nine years ago, when we took our 3-week old youngest daughter to our favorite pediatrician for a small check-up, he noticed a minor irregularity and prepared to perform a small but invasive test on her. I stopped him and asked why he was planning to do so. He answered that it was “the protocol” and would supply him with a piece of important data which he would register in her newly created computer file. When I asked whether the value of this data would determine any specific action to be taken, he admitted that it would not. I therefore asked him not to perform the test to which he immediately agreed. This incident re-confirmed a rule I strictly follow in all my dealings with medical staff to the chagrin of many of them: always politely request that they provide a simple rationale for whatever action they are about to perform. Surprisingly, very often they are not able to do so, apart from quoting “the protocol”. The corollary of this rule for medical tests or examinations, as for measurements in general is:

Observation #5 When you select or design an indicator, make sure you know precisely what you want to know and why.

Even if the price of measuring and communicating a useless indicator is low (even lower than the minimal invasion of my daughter), you would do best to avoid it, as indicators tend to take on a life of their own by bestowing undue importance on the measured quantity.

Observation #6: Indicators, even if selected for the wrong reasons, and therefore useless, will appear important because they’re there.

And, once the indicators are there, you will find yourself playing the corporate-Edmund-Hilary and inevitably climbing the management-imposed-Himalaya, diverting energies from other, more constructive endeavors. This is one of the reasons that we all at times experience a certain unease even as we are exceling according to some set of indicators or other. Deeply, intuitively, beneath our superficial satisfaction at hitting our numbers, some voice is asking: but what for?

In the next post (Part 2) we will discuss how these phenomena play out in organizations’ attempts to measure their level of innovation, as they use indicators such as number of ideas submitted to idea-boxes, number of patents, % of revenues spent on R&D, % of sales derived from new products and other commonly used indicators. We will see that many such standard indicators can be applied usefully, depending on timing and context, and will review several examples, exploring how they can be constructively put to good use.

 

Errors of Exclusion: Two Blind Spots when Planning your Innovation Initiative

Published date: July 25, 2021 в 5:27 pm

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Category: Innovation,Organizational Innovation

We’ve written plenty and posted some in the past about common myths and misapprehensions around innovation. “Not again!”, you say to yourself. For what’s more annoying than some self-important consultant(s) telling everyone how wrong they are. True. On the other hand, as we work in multiple organizations, we just see, and commit(!), so many mistakes that it seems a pity not to share what we’ve experienced, in the hopes of saving this learning-the-hard-way from as many of you as possible. But will reading through lists of mistakes really save one from repeating them? To a certain extent this is so, as alluded to in the famous saying by George Santanaya: “Those who cannot remember the past are condemned to repeat it”. But note that, logically speaking, even if Santanaya was right, this doesn’t necessarily imply that those who do remember the past are immune from repeating it. As anyone who has raised a child will readily attest, some mistakes need to be committed and experienced in the flesh so that one can learn from them. Still, it is my belief that even if you are destined to step with eyes wide open into some traps anyway, being forewarned will help you pay a lower price, learn from the event, and maybe even adjust your course in real time. That is is why we will continue to share with you, from time to time, small collections of mistakes that we witness during our work with organizations.

“Those who cannot remember the past are condemned to repeat it”.

 

This time we will focus on two misconceptions that have to do with the way those in charge of launching an innovation initiative assess their colleagues – their target audience, when designing an innovation program and its execution. Both can be seen as blind spots leading to an exclusive, rather than inclusive approach, often with dire consequences, but both can be overcome with awareness and care, perhaps aided by these practical conclusions and recommendations:

 

1. Black/White Vision:

 

Champions of innovation (and their consultants) often tend to perceive their colleagues through a divisive lens: the cool, positive, usually younger allies-in-innovation, versus the stubborn, probably older, laggards who are getting in the way of innovation with their “resistance”. As is the case with other stereotypes, this one, too, has some obvious basis in reality. But more often than not, those who “resist innovation” are, in their exasperating way, performing one of several useful roles:

  • They may be pointing out to important aspects that should be maintained and safeguarded when the change-tsunami sweeps through the organization;
  • They may be faithfully representing a voice of the customer, who might also find it challenging to adapt to some changes;
  •  They can inadvertently play the role of the proverbial canary in the mine, thus pointing out flaws in your innovation initiative or sensitive areas where you should pay more attention;
  • In many cases they are simply right in their resistance to a specific change, either because in this specific case it makes more sense to maintain the status quo or because it would be wiser to keep searching for a better alternative.

Given these not-so-improbable possibilities, here are a few recommendations:

a.    Listen. Listen, listen. Not fake listening, just to give the laggards the feeling that they are being heard, but sincerely consider the possibility that they may be saving you from yourself. Even if their true motivation is fear of change, they may still be right.

b.    Don’t assume that veterans and older associates will necessarily be harder to convert or less able to contribute to an innovation initiative. On the contrary, they will often be its anchors, supplying the knowledge and experience to make it work. (Disclosure: the youngster writing this post has chugged by his 60th anniversary a few months ago.)

c.    Don’t waste energies convincing recalcitrant managers or units. Learn from them what you can, invite them to join, and if they are still resistant, give them the time and space to join in at their own pace. Time may not yet be ripe for them, or they may be adopting a cautious strategy of first making sure that what you are offering actually works. In the worst case, they will jump on the bandwagon when it reaches cruising altitude (sorry, mixing a few metaphors here).

 

2. Disregarding the Middle:

 

To the perennial debate whether an innovation initiative is best conducted top-down or bottom-up I offer two responses, both frustrating:

  • Both are necessary, to such an extent that you will probably fail unless your plan integrates both approaches. I’ve personally seen each of the two approaches being carried out disregarding the other, always with dismal results. The more common mistake in my experience is the exclusively top-down execution, whereby most of the energy and attention of a corporate unit and its external providers is dedicated to pleasing top management and enlisting their support as expressed in bombastic declarations and budget approvals. I, personally, have tended to err more in the opposite direction, advocating for a predominantly bottom-up course of action, and found to my disappointment, that even though you can achieve wonderful results by empowering the rank and file, if you fail to align with and receive substantial support from top management the entire initiative will sooner or later run out of steam, probably sooner. A combined bi-directional effort is a necessary condition for success. I recommend this as a non-negotiable condition, even if it results in a more complex, and costly, program.
  • The combination of TD and BU, although a necessary condition, is not sufficient. In a typical corporation, or large organization of any kind, it is a third layer, middle management, the company’s backbone, that determines the success of an innovation initiative. Imagine a Marketing/Business/Product Director, say, in an FMCG multinational. Her team is all fired up about an upcoming innovation training, the President of the company is being interviewed in Forbes as an inspiring example of a leader who understands that “now, more than ever, the only constant is change”. So, she is sandwiched between both a BU and a TD innovation-promoting buzz. But while all this exciting discourse is buzzing around her from below and above, who will guarantee that her business unit hits the numbers this quarter? And where will the extra head count come from, if she is made to send her people to yet another course and waste others’ time on innovation forums and conferences? And, as the President halks those futuristic, exciting G3 products that will (hopefully) hit the market in 2024, after sucking up the entire R&D budget, who will fund the tweaks and adaptations that clients are clamoring for in their G2 product orders, without which there is no chance to sell the 500 million USD of the much maligned (in comparison with glorious G3) G2 wares? Middle managers, for the most part, are smart and savvy: they will figure out myriad ways to maintain the balancing act of subtly subduing their reports’ innovation-energies while posing to their superiors as innovation champions, all this whilst squeezing out the business results that everyone’s bonuses depend on. Middle managers are therefore the killers of most innovation initiatives, unless, that is, they are tasked with leading them.
 

To sum up this post’s message about an innovation leader’s two blind spots: no, all those old timers and other innovation-resisters are not your enemy, they should be listened to attentively and brought on board gradually according to their respective timelines and needs, and yes, you do need a Bottom-Up approach and you must combine it with serious Top-Down support, but the mix will only work if your innovation initiative is built around and under the responsibility of your organization’s backbone, its middle management.

What do we talk about when we talk about innovation?

Published date: June 30, 2021 в 11:00 am

Written by:

Category: Innovation,Methodology

When I typed “definition of innovation” into Google the other day, it returned 1,710,000,000 replies, which means absolutely nothing, of course, raising the question why the arguably most influential company on earth has been consistently feeding us with this useless piece of data for so many years. So, I promise to use this very same opening sentence in a future post (repurposing, saving on first-sentence-emissions) about some common popular fallacies around indicators and measurement. But, for the sake of our current topic, the billions mentioned above do give something of an indication of the fact that a lot of words have been spent in attempts to define innovation, and indeed, a quick glance at Wikipedia’s contribution to the subject brings up mentions of various researchers who have compiled lists of 40, 60 or many dozen definitions.

I am going to go out on a limb here and claim that all the definitions that I have seen very much miss the mark, and that we at SIT have been using a simple definition that doesn’t, which I will present to you below. To assess the usefulness of a definition we should start by asking ourselves what we actually expect from one, assuming that “we” are not theoreticians who simply wish to publish a paper on the subject. A useful definition of innovation would allow us to, among other objectives:

  1. Decide if an activity or its result should be considered innovative;
  2. Measure our organization’s “innovation pulse”;
  3. Assess the success of our efforts to become more innovative, or drive our organization in this direction;
  4. Re-direct efforts invested in innovation that seem not to be achieving the desired results.

These are some of the first definitions you will find by googling:

  • Wikipedia: Innovation is the practical implementation of ideas that result in the introduction of new goods or services or improvement in offering goods or services.
  • ISO TC 279 on innovation management proposes in the standards, ISO 56000:2020 [2] to define innovation as “a new or changed entity creating or redistributing value”.
  • Based on their survey, Baragheh et al. attempted to formulate a multidisciplinary definition and arrived at the following: “Innovation is the multi-stage process whereby organizations transform ideas into new/improved products, service or processes, in order to advance, compete and differentiate themselves successfully in their marketplace”
  • Peter Drucker (yes, even the great PD can get things wrong, apparently – A.L.) wrote: Innovation is the specific function of entrepreneurship, whether in an existing business, a public service institution, or a new venture started by a lone individual in the family kitchen. It is the means by which the entrepreneur either creates new wealth-producing resources or endows existing resources with enhanced potential for creating wealth.

Why are all these definitions inadequate? Each has its particular deficiencies, but they also share a common defect. They all suffer, to a varying extent, from a series of nested biases:

A bias in favor of organizations —————> rather than human endeavors in general, individuals, families

Within organizations, a bias in favor of businesses ————–> versus communities, governments, criminal, educational

Within businesses ———————> in favor of products, rather than services

Within products ——————–> in favor of technological products

Within technological products ——————–> in favor of hi-tech

Within hi-tech ————————-> in favor of R&D

 

So, if you are an engineer in a hi-tech startup developing a product with the goal of entering the market and making money – plenty of these definitions can plausibly describe what you are doing or aiming to do. On the other hand, none of them is adequate for capturing or evaluating, for example, the following activities, in descending order of relevance (all of them based on personal experience in my role as innovation consultant and facilitator):

  1. A marketer in the same startup, rethinking their go-to-market strategy;
  2. The startup’s CFO, planning her presentation to a potential investor;
  3. The CEO, dealing with her difficulty in communicating a pivot in strategy to the company’s employees;
  4. All the above-mentioned functions in a traditional industry, manufacturing wooden furniture, for example;
  5. A project manager in an NGO, searching for a new way to effectively distribute contraceptives in rural India;
  6. An ad-hoc collective of activists figuring out their next steps in an equal-rights campaign on the streets of a large city;
  7. An ex-con trying to crack the code of a safe (this one I refused to collaborate on);
  8. A father trying not to repeat his regular response, that has obviously not been working too well, to his teenage daughter (this one was pro-bono, auto-pro-bono).

Try any of the definitions from the googled results on any of the items on this list and you will immediately note how increasingly inadequate they sound as you advance through the examples. Applying the same logic, you can easily imagine myriad additional examples excluded by the standard definitions, rendering the definitions useless for what are probably 90% of human activities that could, in principle, be innovative. Consider, however, the following definition, formulated by us at SIT and refined through years of use:

To innovate is to think and act differently to achieve your goals.

Let’s zoom into each of the four key elements of the definition, in turn.

  1. Innovation is first and foremost the fruit of a cognitive, thinking process. It requires conditions, both emotional and material, but the first and often-overlooked condition is supplying people with time to think. “Think”, not as in “how and what do I quickly answer to my boss’s complaint?” or “what 15 things do I need to do today and how the hell will I make time for them all?”, but “think” as in taking time off from one’s incessant race to reflect on it from above or from the side.
  2. Whatever you are doing, you’re not innovating if it doesn’t translate into action. Beware the shiny PPT presentation of elaborate organizational flowcharts describing “our new innovation process”: seek concrete actions leading to implementation.
  3. One of our key rallying cries is: Don’t do innovation – rather, innovate in what you do. Innovation is a means and not an end in itself, and therefore, an action can be considered to be innovation only inasmuch as it supports or accelerates your efforts to achieve one or more of your goals. Innovation leaders, units and consultants often flip this causal relationship and act as if innovating is the goal. This is only natural since it actually is the goal – for them. But an organization needs to remember that actions and initiatives can only count as innovations when they promote the organization’s objectives. This is true also of individuals or teams. Note that there is nothing in this definition that favors “value for the market” or the role of customers or any of the corporate-speak business-oriented language. If your goals pertain to the realm of business, then innovation should lead to business results. If your goal is, say, happiness then, for you, an action is innovative if – in addition to the other three characteristics mentioned in the definition – it increases happiness.
  4. Many actions require thinking and promote the goals of an individual or organization and yet it would not be useful or productive to consider them to be examples of innovation. In fact, most of what members of an organization routinely do falls into this category. Doing your job properly, improving your processes, using Quality tools, all these important and commendable activities can contribute much to an organization, and yet we would still not wish to define them as innovative. The last and crucial ingredient in our definition, therefore, is that your thinking-based and goal-promoting action must stem from thinking differently. This, of course, begs the question of what will be considered as different enough to count. We offer a simple and powerful answer: thinking differently means breaking one or more of your Cognitive Fixednesses.

So, introducing this concept into our definition we get:

You innovate when you think and act in a way that breaks your fixedness leading you to achieve your goals.

This working definition lends itself to numerous practical applications. It can, for example, be immediately translated into a useful pair of criteria when you are asked to approve submissions of ideas or achievements to an internal innovation competition in an organization. Those who submit an entry are asked to demonstrate:

  1. The impact of their project (potential impact if the competition is among ideas; measured impact if, as we prefer, prizes go to implemented projects rather than ideas);
  2. Which fixedness(es) had to be broken in order to come up with and/or implement their idea.

These two criteria, when applied jointly, easily filter out hairbrained schemes without demonstrable results (or the potential thereof) and on the other hand embrace candidates from any type of activity in the organization that supports its strategy and goals, without bestowing preference to R&D or other usual suspects. Our definition is not perfect, of course: definitions are notoriously elusive and slippery, and tend to circularity. One way of assessing a definition’s value is by evaluating to what extent it captures all phenomena one wishes to include under a term and how effectively it excludes those one doesn’t. The definition presented here performs well on both counts, I believe, including a very wide range of activities versus the organization-business-product-technologically biased alternatives. It also helps filter out useful but non-innovative activities and even points to a practical direction for those who wish to nudge their current activities towards a more innovative path.

A crucial element in making this definition operational is obviously a clear and communicable understanding of the concept of FIXEDNESS. In future posts, we will delve deeper into this concept, so central to the very essence of innovation.

5 Key Elements in Planning a DT Initiative

Published date: June 23, 2021 в 5:16 pm

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Category: Digital Transformation,Innovation,Organizational Innovation,Strategy

We opened this series with two posts dealing with the barriers to implementing Digital Transformation in your organization. “Why start with the negative?”, one may ask. First, it is often most useful to discuss the difficulties involved in a certain endeavor, especially when the general tone of the topic is one of unabashed hype. Second, as with other innovation-related endeavors, a major managerial error in DT is jumping into a buzzy-sounding initiative while disregarding its potential pitfalls and therefore doing so without proper commitment and preparations. One key message of posts 1&2 in this series is, therefore: avoid launching a DT initiative if you are not willing to confront the challenges, that will certainly arise, with determination.

In this post we present 5 Key Elements to consider as you prepare to launch your DT initiative. In future posts we will zoom-in to some of them in more detail.

Key Element 1 – Goals and objectives

Why are you launching this initiative, and what are you trying to achieve by it? It may seem redundant to even mention this obvious rule, given that it is the basic starting point for any activity. But DT efforts, specifically, often tend to be driven by the wrong motivations which can doom them from the outset. This is a short list of some of the common drivers for launching a DT initiative:

1.    Public opinion, boards, Wall Street, stakeholders are demanding it;

2.    Competitors are embracing it, and this threatens to give them an advantage;

3.    Talent flows to organizations that are more digital;

4.    Customers demand it;

5.    Suppliers become digital;

6.    Legacy systems and technologies are becoming obsolete;

7.    FOMO, including both the frivolous and the serious versions.

All and each can be legitimate, but only motivations that are exposed and shared can serve as guides for choosing the right path forward.

Key Element 2 – Where are you now?

It is useful to see the path to Digital Transformation as consisting of three stages:

1)    Digitization – roughly, transforming your paper records into bits and bytes;

2)    Digitalization – implementing the tools and processes that allow access and utilization of the digital information;

3)    Digital Transformation – rethinking and redefining your processes and your modus operandi to make the most of digital possibilities and to adapt to the needs of a digital environment.

Organizations often mistake steps 1 or 2 with DT, whereby they not only miss opportunities for reaping the full rewards of DT, but often suffer damage by digitalizing processes that work better in analog. It is therefore crucial to clearly identify where the organization is at the outset of the initiative. This is less obvious than it may seem, given that business units or departments of the organization can be in different stages of the digital journey, that Stage 2 can superficially feel like a transformation although it isn’t really, and that some stakeholders may very much resist the implications of admitting that Stage 3 is still in front of them.

Key Element 3 – What do you aim to change?

Which area(s) will be transformed?

When you say your organization wants to “be more digital” or to digitally transform itself, you must define what it is that you are attempting to transform:

o Products and offerings   o Business models           o Productivity

o Processes – internal         o Processes – external     o Decision making

o Communications – internal and external                o Other 

Some of these may be difficult to transform without changing adjacent processes, others can be dealt with independently. It is sometimes better to go about the transformation gradually, rather than attempting the change all at once. Both approaches have their pros and cons.

What’s going to be D about it?

Even when a certain part of the business has been selected for digital transformation, for example product offerings, even then there are a variety of aspects that can be tackled and transformed and, in many cases, only some of them will. A full transformation of, say, a specific product or process into digital may, and often will, include changing how you:

o     Sense                      o     Collect                         o     Aggregate/store

o     Analyze                  o     Communicate          o     Visualize

o     Recommend        o     Act

 

Key Element 4 – Technology

When we work with a company to assist in DT, we find it useful to compile lists of technologies. The lists tend to vary somewhat according to domains and with time. In the list below there are four main families with 16 technologies (fluid number) that are often applied to achieve DT. It is not realistic to expect that any single person will be proficient in, or even just deeply knowledgeable about, all of these, but it is becoming increasingly necessary for every executive to have at least a superficial understanding of what they each mean, enabling them to turn to relevant experts with intelligent questions to assess potential threats and benefits for their area.

1.    Thinking and analyzing

a.      AI – Artificial Intelligence

b.      ML – Machine Learning

c.       Neural Networks/Deep Learning

d.      NLP – Natural Language Processing

2.    Vision and processing

a.      AR – Augmented Reality, VR – Virtual Reality, and MR – Mixed Reality

b.      Computer vision

c.       Image processing

3.    Computing and Communicating

a.      Big Data/Deep Data

b.      Cloud

c.       5G

d.      Quantum computing

e.      Social media

4.    Sensing and making

a.      IoT

b.      Industry V4.0

c.       Robotics

d.      Wearables

Key Element 5 – Behaviors

As is becoming increasingly obvious, even to the more technically inclined, digital transformation depends less on the technologies deployed and more on the people employed in implementing them. The mindset shift required for a digital transformation is elusive and can be understood as the adoption or strengthening of a set of crucial behaviors. The following, non-exhaustive list includes some items that are recommended independently of digital context, while others are more D-specific:

  1. Be flexible, break fixedness;
  2. Focus on data: collect it, store, analyze, explore, etc.;
  3. Beyond listening to the customers: interact with the customer in exploratory mode. Both internally and externally, engage employees in new digitally transformed platforms and engage customers to use them.
  4. FFD – Function Follows Data/Digital: search for data, collect it and analyze it even before you understand its potential uses and benefits. This is necessary to overcome the chicken-egg problem of no budget for collecting data until you can prove benefits of it.
  5. Everything is a pilot: pilot as soon as possible, even partially (MVP style), progress from pilot to pilot, treat any version as a pilot for the next.
  6.  Solutions can come from a variety of sources, both internal and external: develop internally, hire the knowledge, assign to freelance, outsource to vendor, acquire tech, acquire company, partner with academia, JV, and usually a combination of some of the above.
  7. Beware overload of data and technologies – do not assume that their existence will guarantee wise usage or any usage.

Following our two posts on barriers to DT, in this post we have reviewed 5 key elements to consider when setting out on a digital transformation journey. In future installments, according to your questions and comments, we will zoom in and expand some of the elements, sharing examples and tips.

Digital Transformation – the SIT version – part 2

Published date: June 16, 2021 в 5:00 pm

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Category: Digital Transformation,Innovation,Organizational Innovation,Strategy

In our first post on the difficulties faced by organizations attempting Digital Transformation, we shared a few sentences about each of 4 common barriers:

1. It is truly difficult to trust experts on DT, especially the “experts”.

2. Mixed signals from top management.

3. Security concerns (real and imagined).

4. Ignorance of relevant technologies.

 

Here are 6 more, completing our not-comprehensive list of 10 Common Barriers to Digital Transformation:

5

Regular resistance to Innovation, probably amplified. In other posts you are welcome to read about some of the multiple types of resistance that people exhibit towards any kind of innovation. They all apply to Digital Transformation, just as they do to any attempt to change processes and habits, in general. But it seems that for many people innovation of the digital ilk can be even more frightening than other variants, maybe due to the fact that many of us feel threatened anyway by what feels like a digital invasion in all walks of life. We are bombarded with digital information, we fight with our children about what seems to be their excessive immersion in the digital sphere, we read of, and sometimes experience the imminent dangers and ethical dilemmas of an increasingly digitalized existence. DT at work therefore seems to be yet another front in a losing battle.

6

Problems related to interfacing with existing IT technologies and organization (real and imagined). Most companies striving for DT do not attempt to jump directly from the Stone Age into digital. Most, or even all, have legacy IT systems and whatever new elements will be introduced will necessarily have to fit in with existing infrastructure, hardware and software. This implies: a) a need to allocate additional budget (good for IT, less attractive for Finance); b) a threat to the professional authority of current internal IT experts; c) bugs and clashes between old and new systems; d) an opportunity for renewing aging systems, which creates a dilemma of how far back to go with replacement, versus adding new technologies on top of existing ones. These dilemmas can paralyze the entire DT initiative.

7

Lack of clear ownership: regular business owner versus IT/tech lead, versus owner of “Digital” if there is one. In one organization you see a digital expert brought in and put in charge of “Innovation” without any knowledge or previous experience in the latter, while in another an innovation expert is assigned the responsibility for a “Digital Transformation” project she has no ability to lead. In both cases the reasons for the decision are an attempt at efficiency (“can’t waste two headcounts on the fluffy stuff”) and a foggy understanding of the differences and interconnections between the two topics (“he’s an expert on digital, that’s what innovation is all about” or “she’s an innovation expert, she can cover the digital transformation part”). IT will also be angling for a position at the DT table (“it’s all about IT, the systems we’re in charge of”), and HR wants their voice to be heard (“it will all depend on the people we hire and on upskilling digital capabilities”). They are all obviously right, often leaving the organization without a clear leader for DT, or worse, with several.

8

Lack of structured data to start building on. Imagine my surprise when the VP IT (and responsible for her organization’s DT initiative) of a leading HMO in the US confided in me that, while they are truly committed to a genuine DT process, she expects the interesting steps to kick-off at best only within a couple of years since they are currently grappling with the uninspiring task of converting their (literally) millions of medical records into digital format. Even technologically oriented companies tend to have a huge installed base of “dumb devices” that were never designed to collect data, or minimally so, or produce unstructured and difficult to use data. This lack of accessible data often makes it difficult to even imagine digital offerings (the “what”) let alone how developers should go about tackling the challenge (the “how”).

9

“Digital” is seen as an add-on, or a translation process to be applied to products and offerings. In 2004 we worked with a large publisher whose management had the foresight and courage to push strongly for “more digital”, quite a while before this had become the ubiquitous trend it is today. But, alas, their strategy was to create a Digital Team that received all the analog materials at the end of their development process to “convert them into digital”. Surprisingly, even today this is still common practice in many companies, where digital is seen as a kind of different language to which specifically trained experts will translate the regular (analog) products, processes, systems, or communications. First, this approach dramatically limits the potential benefits of DT, since you can only translate into digital what you were able to imagine in the analog world, rather than creating and inventing using digital possibilities built into the process. Second, the approach often creates inferior results since many analog-conceived concepts do not translate well into digi-speak.

10

Timelines and pace: development cycles do not fit the rhythm of change in digital technologies, nor the pace of change in customers’ preferences and habits. Most companies have a single well-structured R&D process, if at all. When they engage in the development of digital offerings, or introduce digital elements in their regular development, they often tend to utilize their existing development process, stage gate structure or other process management and control mechanisms. Even organizations that adopt Lean Startup or other agile methods often embed them into their overall approach due to lack of understanding at top management levels that the rules of the game are different in a digital context.

We’ve seen, therefore, that there are (at least) 10 barriers and stumbling blocks to a successful Digital Transformation. Luckily, we have developed a special pixy dust that can be sprinkled on databases and clouds to…. OK, just kidding. But in consequent posts we will share some thoughts and guidelines that are useful when engaging in this challenging task.

Digital Transformation – the SIT version

Published date: June 9, 2021 в 4:55 pm

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Category: Digital Transformation,Innovation,Organizational Innovation

In the past 2-3 years, many of the companies we are in touch with have been dealing in one way or another with Digital Transformation. This can happen for several reasons, some more relevant and logical, others less so. Among them: pressure from owners, stockholders or the public; the stress of seeing competitors enter the field; new hires (usually younger) flowing in with both knowledge and aspirations in the digital sphere; customers’ expectations (realistic or imaginary), and more. While working and talking with these companies, we at SIT have been accumulating quite a bit of experience in helping organizations overcome the challenges and reaping the rewards of Digital Transformation. Among other insights collected in our DT work on four continents, we have identified 10 Barriers that hinder these efforts. In this post we are happy to share 4 of them, with a few notes on directions for overcoming them. In the next posts we will share some of the others.

You will encounter a variety of barriers and road bumps:

4 (of 10) Barriers for Achieving Digital Transformation

1.

It is truly difficult to trust experts on DT, especially the “experts” that abound, because they (we?) all have biased POVs (and are probably all trying to sell you their wares, hard or soft). The first step in searching for an expert is to clearly define an expert for what you are looking for. Companies engaging in Digital Transformation tend to rush to providers of digital systems and services: transferring to the cloud, designing snazzy apps, implementing blockchain, before they have a clear and coherent picture of what they are trying to achieve and why. They tend to forget in spite of the warnings, that DT is first and foremost about transformation, and only then about digital.

2.

 

Security concerns (real and imagined). It is true that the more digitally sophisticated your processes become, the more vulnerable they are to tampering and cyber-attacks, and these are not at all imaginary. The recent ransomware attack on the Colonial Pipeline Company, that stopped fuel flow to a large chunk of the US East Coast for over a week, was just a frightening reminder of the hundreds of similar attacks that have probably occurred this year on private companies’ IT infrastructures. The good news is that when cyber security considerations are built into digital practices from the outset, risks can be strongly mitigated. And, yes, it’s safer to ride in horse-driven carriages but were we supposed to give up on motorizing our company fleets because of this?

3.

Ignorance of relevant technologies (and terminology) often accompanied by a fear thereof (the “Quantum Computing Effect”). In our experience there are about 15-20 technologies that one needs to know at least a tiny bit about in order to intelligently assess your DT status and potential. Quantum Computing, for example, is probably not something you need to implement in the next year or two, but you would be surprised how soon it could revolutionize your field (pharma developers, for one, should be, and probably are, very alert to the possibility). Our list of 18 technologies to watch is not exhaustive but a good start.

 

4.

Mixed signals from top management:

a. The “ambidextrous” effect – the demand that you keep selling current offerings like crazy and at the same time invest plenty of time and energy on DT;

 

b. Management demands DT but is itself lacking in all digital or transformative understanding and behaviors;

c. Management demands DT but is unwilling to invest substantially before you present them with a concrete business case, although how you can be expected to produce such a business case without receiving some budget for (at the very least) collecting and analyzing data is anyone’s guess.

Dealing with (higher than you) management is notoriously difficult, obviously, but we find that delicately pointing out the abovementioned points can facilitate what can turn into a constructive conversation.

In upcoming articles and posts, we will share some of the other barriers as well as some of the methods and techniques we apply to the challenge. We are also always happy to get on a short call, with those who would like to pick our brains or use us as a sounding board on anything to do with thinking and acting differently to achieve your objectives.

Developing Herd Immunity to Innovation

Published date: March 15, 2021 в 4:30 pm

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Category: Innovation

How did the terms “brainstorming” and later on “design thinking”, become synonymous to “ideation” or “innovation”? This is a strange phenomenon, made doubly puzzling by the fact that both BS and DT are respectively pretty useless and not-so-helpful when it comes to driving people, teams and companies to break their usual ways of thinking and create true novelty.

Brainstorming, famously invented independently but near simultaneously by Alex Osborn and Walt Disney in the early ‘50s, played an important role in its early days in promoting creativity and innovation, especially in the corporate world. Formerly downtrodden executives suddenly received a “license not-to-kill” and more importantly not-to-be-killed that allowed them to speak out their ideas in relative safety. In the closed hierarchical culture of those times, this was invaluable and contributed to a true cultural revolution. Some 70 years later, BS remains a tool that may help motivate participants to be active in a discussion (if they are not absolutely fed up with the process, as often happens), drive them to share ideas they already have (if they haven’t had plenty of opportunities to share them, as is the case in many organizations these days) and promote team-building. So, what is there not to like? Brainstorming is harmful only inasmuch as its proponents claim that it is a dependable method for generating new ideas. It isn’t, and this is confirmed time and again by the experience of its corporate users. A quick search for “research showing that brainstorming doesn’t work” provides plenty of material to substantiate this fact.

Why, then, does BS continue to be used nearly synonymously with “ideation” and “innovation”? There are several possible explanations. Here we will mention only two, that are of special interest, since they also partially explain the allure of brainstorming’s heir: Design Thinking.

1)     BS and DT both evolved with the support of strong, cool proponents with a strong knack for PR (the ad industry and “the IDEOs” respectively).

2)     Both BS and DT are outstanding at giving their users the illusion that innovating is easy and fun.

Design Thinking is, obviously, more complex than BS, and is useful in many ways. In fact, anyone engaged in innovation would do well to learn and utilize the method. Its false claim is more subtle than that of BS, and is actually related to BS. There are various ways of describing DT, but a reasonable depiction divides the method in three main steps:

1)     Empathize and Define Needs

2)     Ideate, challenging assumptions

3)     Prototype and Test

DT does an admirable job in steps 1 and 3: it markedly enhances the abilities of individuals and teams to gather insights and get into the user’s shoes. This is invaluable for any business or anyone who aims to supply a service or product. DT has also greatly enriched innovation processes, and thinking in general, by emphasizing the importance of visualizing and concretizing ideas through prototyping, and to the courageous practice of going out and testing ideas.

It is only in step 2, that DT falls, literally, into the BS trap. For what does DT offer as the crucial step between beautifully garnered insights and compelling prototypes? What does Design Thinking propose as a method for “ideating” and challenging assumptions? Brainstorming.

Design Thinking is, therefore, a useful framework for tackling innovation. It just lacks a key component, the heart of the process, i.e. a trustworthy method to break out of one’s fixed ways of thinking, and thus create novelty. There would have been no harm done, if the originators and evangelists of DT would have presented it for what it is: a useful collection of tools for harvesting insights, for visualizing and for prototyping, placed within a sensible 3 (or 5) step process. But for some reason the world was also asked to buy the notion that in order to innovate:

a)      Everyone needs to think like a designer, and

b)     All you need to do is empathize and then prototype

To this they added, what in terms of PR was a stroke of genius:

c)      The best way to innovate is to have fun.

But, in fact:

a)      Why should the role of designers, cool and visual as they are, be a model for a CEO rethinking her company’s strategy, for a scientist manipulating a molecule or for a teacher coming up with novel ways to teach a history class? There are, indeed, some aspects of innovation, especially as it relates to product development, that are similar to the work of a designer, but that is a far cry from claiming that all innovation should be conducted as if it were a designers’ task.

b)     Empathic insight collection is crucial, as is prototyping, but the key element, the missing middle, is breaking one’s fixedness. This can be done with structured tools. We recommend ours, obviously (SIT), but any effective non-Brainstorming method will do the job. Without it, you will most probably find yourself rehashing your existing ideas with cosmetic changes.

c)      Having fun in life is obviously better than not having fun. But is it conducive to innovation? In a certain, very limited sense, this is true. Having fun is energizing, and a group that is enjoying itself may persist longer on a given task. But achieving true innovation is nearly contrary to “having fun”. True innovation requires changing the way one thinks, and that is a painful endeavor, and the motivation to do so more often than not arises from discontent and discomfort.

Why, then, have Brainstorming and Design Thinking cornered the innovation market, becoming synonyms for ideation and innovation? They are easy to adopt, give an illusory sensation of easy wins and have useful benefits that can easily be mistaken for innovation. And, of course, great PR has created a herd phenomenon, with the perverse result of weakening innovation instead of enhancing it.

What is needed is a rich framework, combining useful elements of empathic design, visualization, prototyping and experimentation of the Lean Startup ilk with a robust methodology for breaking out of existing thought patterns. In the past few years we have accumulated experience in creating such “braided” formats, based on SIT’s structured (and strongly non-brainstormy) approach to ideation, bringing predictability and method to the seemingly mysterious core of the entire innovation process.

Published originally as a post for Innov8rs.com:

https://innov8rs.co/news/how-executives-develop-herd-immunity-to-innovation/

The No-Forecast-Kit for Dealing with the COVID World

Published date: May 20, 2020 в 2:00 pm

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Category: Innovation,Methodology,Problem Solving,Strategy

A Short Article, a Toolset and a Loooong List of Vectors

The purpose of this post-COVID Kit is to help guide your thinking and discussion about a crucial issue: how should one prepare for and live with the changes brought about by the global pandemic. In the first two pages, I describe a certain approach to the issue, of which the gist is: do not attempt to forecast what is going to happen, but pay close attention to certain forces, vectors or trends, and figure out how they can influence you and your organization, and then try to proactively engage with these developments. The second part is a set of questions, based on SIT’s methodology for innovation, that allow you to convert the list into a practical exercise in thinking about the future. The third, and last part is a list of 23 topics, each followed by 5-10 bullet points, each of them pointing to at least two directions, often contrary, in which some force or vector can play out in the coming months or years.

Contents

Article

Toolset

A. Exploring the list

B. Breaking Mental Fixedness*

1. Task Unification*
2. Subtraction*
3. Qualitative Change*

List

A. Individuals, Families

1. Mindset and Attitudes
2. Mental Health
3. The Family

B. The Collective

1. Society
2. Education
3. Communications
4. Government
5. Religion/Spirituality
6. The Arts
7. Travel and Tourism

C. Health, Science, Technology

1. Public Health
2. Science
3. Technology
4. Data

D. The Globe, the Planet

1. Sustainability
2. Global Politics
3. Global Economy

E. Work, Business

1. Work, employment
2. Business: General
3. Retail
4. Supply chains
5. Transportation
6. Manufacturing

Article

I am not a futurist, nor are my colleagues at SIT – Systematic Inventive Thinking. As famously remarked by Niels Bohr, “Prediction is very difficult, especially about the future”. And much more so, when a cataclysmic event of global magnitude is unfolding as we write. What we specialize in, and what this document is about, rather than exploring predictions about the future, is attempting to shape this future, even if on a modest scale.

There are two confounding aspects of the attempt to forecast even the near future in 2020. The first is the well-known butterfly effect, but with billions of butterflies fluttering their wings simultaneously in an unprecedent manner. Thus, the Mozart of 2040 may have found her vocation when her mother, after 30 days of quarantine, out of desperation, downloaded a piano-teaching app to calm the noisy 3-year-old. The second is the appearance of strong and often opposing vectors that seem to cancel each other out, but, in fact, do not. So if a million couples who otherwise would have stayed together are driven to divorce, while another million couples about to divorce rediscover the bonds that held them together and don’t, in term of global statistics nothing has changed, but for two million families life’s course has swerved dramatically.

But, even though the ability to forecast with a high probability of success is very limited, it is still extremely useful, even necessary to pay close attention to some strong vectors or forces that are emerging as a result of the virus and, even more so, the various manners in which the world has chosen to deal with its effects. There are two prevailing views as to the changes: they, too, are contradictory, and yet both can prevail at one and the same time. One view holds that in the end, most people, and definitely businesses, are looking more than anything to resume life as it was pre-COVID. Expect, therefore, relatively small changes, mainly temporary adjustments. The other party claims the opposite: the pandemic, with its imposed restrictions and behaviors, has triggered changes so fundamental, that humanity cannot but evolve into a state of “new normal”. I use the expression “party” advisedly because I believe that both views have an element of “wishful forecasting”; those who wish to maintain the status quo are attempting to will reality to do so, and those who see an opportunity for – finally – a major upheaval, are loath to give it up. In this document, true to the spirit of our approach, we claim that both can, in a sense, be right at the same time. Each view represents a strong and potent force pushing in a contrary direction, and as reality will be shaped by the interplay between both, it would be wise for any individual, group or organization to consider the potency of both without trying to conjecture which will prevail.

Below, you will find a non-exhaustive list of 23 areas in which one can expect the world to change following the COVID crisis. There is no attempt here to predict what will eventually happen in any area, only to map some relevant vectors of potential change in each of them. In many cases, the vectors are contrary in their directions, which raises two questions: what is the value, or is it not tautological to claim that, for instance, people will either strongly yearn and search for the contact of other humans or will develop a defensive stance of distancing themselves from their fellow inhabitants of the globe. Our claims are that both vectors are very likely to be felt post-COVID, and that they will not necessarily cancel each other out. The way this will unfold is difficult to predict, but if your business or organization depends on prospects’ relation to other humans, for example, you would be wise to consider that many of them will probably be living with the conflict of both feeling strongly the need for human contact, and fearing its risks and consequences.

Another example: Say that you need to make decisions that depend on the future of shared rides globally. Do we predict an increase post-COVID, with a strengthening of the Ubers of the world, or rather a decrease, as new models emerge, or passengers return to pre-rideshare habits? The most useful answer may be a combination, or at least an invitation to consider at least two tendencies. The first is an aversion of potential riders to spending time in a confined space with people of whose health they have no information or guarantee, touching surfaces that have probably been in contact with other strangers not so long ago. The second is a set of economic pressures that may push both users and drivers to depend even more on shared rides, the former due to difficulties in owning a car and the latter as their only alternative for employment. In addition, the evolution of shared rides may be affected also by other tendencies, with their own combination of (sometimes conflicting) vectors: will the post-COVID world be (even) more unequal, or will this crisis be an inflection point, by exposing the perils of inequality and the interdependence of rich and poor, thus pushing towards creating a more level playing field?

Thinking about the food and beverage industries, to look at yet another case, can we expect a strong consumer tendency to seek healthy food, finally acknowledging that rather than trusting their fate to vaccines and antivirals one’s first duty towards oneself is to keep healthy, by, among other means, eating fresh and natural food? Or, alternatively, will we see a surge in consumption of fast (and junky) food, due to fatalism (“Why should I give up the food I like, if a random virus can kill me anyway?”) or to a habit created or strengthened by weeks upon weeks of ordering pizzas and hamburgers in quarantine? Our prediction: both. Recognizing these two highly probable and opposing vectors, a corporate player in this space could reach one or several practical conclusions, all logically, if not always ethically, valid. For instance:

a)      Gamble on the healthy option, using the opportunity to dare not only to supply the partly-met need of health seekers but also to lead the laggards into healthy consciousness.

b)     Play the fast food card, not necessarily cynically, but catering to the “new lazy” who absolutely refuse to cook, by competing with take-aways and expanding the variety of easy food for the home.

c)      Recognizing both tendencies, find ways to provide offerings that answer both the desire to be healthy and the tendency to outsource household tasks.

d)     Lead a revolution in the role of food manufacturers in society and the economy, by recognizing their critical share of the responsibility for public health.

e)     Disregard the health issue, and focus, instead, on convenience and/or safety as the greatest consumer concerns.

We see, therefore, that even lacking a crystal-ball-clear view of the future, one can engage actively in creating it. Disregarding COVID- related developments comes at a risk, since what can be expected with high probability is that COVID will cause a ripple effect of strong forces or vectors for change. But, contrary forces at play again, when imagining the unfolding of exciting and/or frightening (depending on one’s imagination and inclination) futures, one should never underestimate the strength of individuals’ and societies’ tendency towards homeostasis, a tremendous pull to what feels like the safe equilibrium of old and comfortable habits.

To summarize: trying to forecast – futile; but watching trends, interpreting them, figuring out possible effects and proactively attempting to adapt and influence the future – a must.

 

Toolset

There are multiple ways to use the list below, some of them are presented here, divided in two modules:

A)      A set of questions that help in exploring the list systematically;

B)     Several tools for challenging your assumptions and opening your minds to come up with inventive ideas to deal with the phenomena described in the list.

A. Exploring the list

  1. Read though the topics, enjoy entertaining your own thoughts, guesses and predictions about each area;
  2. Identify those areas that are relevant to you, your organization, your business, and ask yourself what the probabilities for certain futures are, and what would their emergence mean for you;
  3. Select one or two areas that don’t feel directly relevant to your organization, activity or business. Challenge yourselves to figure out whether and how these seemingly unrelated forces will in fact influence you;
  4. Most challenging, but potentially most rewarding: which futures do you feel strongly about, and what can you do to increase the probability that they, rather than their alternative, comes to pass.
  5. Focus on an area/topic and add vectors and forces to the list. Discuss them as well.
  6. Review the “positive” vectors: how can you strengthen them?
  7. Review the “negative” list: how can you overcome these?

B. Breaking Mental Fixedness*

In this section, a set of mental tools is presented, that allows, in addition to stretching one’s mind as recommended above, to tackle head on one’s “mental fixednesses”, the patterns that restrict a thinker to old and well-trodden paths. There are additional tools in the SIT method that can be applied as well, but these are some of the most obvious candidates.

      1. Task Unification*

a) Select a certain force or vector, which intuitively seems to be working in your favor in some way;

b) Ask yourself: can I see this vector as a resource? Meaning, can I make it work for me?

i) By acting to promote one of my objectives?

ii) By acting to promote something positive that I had not been aware of?

c) Now select a vector or force that intuitively feels as if it can affect you negatively.

d) Repeat the resource exercise (1b) with the “negative” vector, but this time you will need to overcome your intuitive negative sense of this vector, since you will be searching for ways to employ it in your benefit. Ask yourself:

i) Can this, supposedly negative vector, actually work in my favor?

ii) What would I need to do to make this happen?

       2. Subtraction*

a. Some of the vectors, trends or forces will cause certain elements which seem crucial to you, your activity or your business to simply disappear, or be radically reduced temporarily (e.g. tourists for an airline, during quarantine). By browsing the list, take note of these cases as they apply to you. This disappearance we call a Subtraction.

b. For each of these cases, ask yourself the counter-intuitive question: what can you gain, how can you benefit, and which opportunities will open up thanks to this subtraction? Can it be that, even when the temporary subtraction ends (say, tourists return), you can continue doing some or all that you put in place when they were gone?

c. Ask yourself the following counter-intuitive question: COVID is forcing you to do without element X (say, face-to-face meetings), and you are learning how to manage with this subtraction, and even find benefits in it. What if COVID would have forced you to do without element Y (say, without meetings at all, or without internet connections)? Can you think of benefits for that as well? Is it worth experimenting with this option?

        3. Qualitative Change*

a. Each force, trend or vector you review immediately conjures in your mind a certain chain: if A will indeed happen, so will B. Sometimes B will be negative, which means that you will automatically view A as negative as well (since it seems to inexorably lead to B). Identify an A that seems to lead to a negative B.

b. Create two sentences to use as triggers for invention:

i.           Given A, how can you prevent B from happening?

ii.           Can you imagine a context or situation in which: the more A the less B? Meaning, even though as A grows there normally is more of (negative) B, can you imagine a situation in which the relationship is flipped so that the more A the less B?

c. Repeat (3b) with other forces or vectors.

*These tools and principles are part of the SIT – Systematic Inventive Thinking methodology. Read more about them, and their use, in www.sitsite.com

List

This list of forces, trends and vectors covers 23 areas, that are divided into 5 general groups (A-E). It is obviously not exhaustive, nor is it meant to be, but rather covers a wide range of points of view that can serve as triggers for a productive discussion of the Post-COVID world, with or without the recommended Toolset. The list is long. Browse it at leisure, perhaps turning both to some areas that are directly relevant to what you care about, and some that initially feel further away. You will probably be surprised to find that contemplating some of the latter can turn out to be just as productive.

A. Individuals, Families

       1. Mindset and Attitudes

a. Work-life balance. Millions desperately returning to work after being kept away for months versus millions discovering the joys of spending time at home rather than at work.

b. Approach to nutrition: realization that the best way to protect oneself is by maintaining good health, and this is possible through nutrition, versus, health can always be maintained through medication, versus, live as you please and trust the system to treat you when you fall ill.

c. The natural quest for convenience maximized in certain societies where all basic needs are delivered immediately with a digital click, versus the need to factor in safety as the overriding consideration in consuming, and balancing these requirements with cost.

d. Invitation to humility – human beings cannot control everything, versus a deep-seated human hubris – the belief that in the end our science and technology prevail.

e. Belief in science: in times of crisis we can only trust our scientists, versus “science failed us when most needed, and scientists can’t even agree among themselves about the basics of the pandemic”.

f. Individuals feel debilitating uncertainty, living a situation akin to cultural shock, as regular assumptions cease to apply to reality: a strong urge to surrender your decision making to authorities, to those “who know”, versus an impulse to seal out disturbing information and trust one’s intuitions.

g. Impressively, extremely complex and multi-faceted problems can be broken down into sub-tasks and solved by a distributed multi-team effort, versus, even the combined efforts of global talent and technology could not overcome a simple virus.

h. Feeling of dependence on humans, versus dependence on technologies. When push comes to shove only our fellow humans can give us the strength and energy to survive, versus: distanced and split from our fellow humans, our reliance on technology is near total.

i. Apart from phenomena that defy the laws of physics, will we ever be able to say again, of anything, even the wildest scenario, that it is improbable, much less “impossible”?

j. Has this crisis completed the rewiring of our brains, creating humans who can capture and digest only the briefest and simplest twitterized communications, or have we benefitted from this time of relative tranquility and immobility to read, think and discuss profoundly about important issues?

       2. Mental Health

a. Immediate results of the crisis: depressions, anxiety, solitude, or recognizing one’s internal strength and abilities to adapt and overcome adversity.

b. Usage of psychiatric drugs: increased dependency, versus forced cold-turkey and freedom.

c. Addictions: increase due to stress and depression, discontinued rehab programs, solitude, versus forced rehab through scarcity induced withdrawal.

d. Stress levels at record high due to frightening messages and general feeling of impotence, uncertainty and lack of safety nets, versus finding calm in the tranquility of one’s home and proximity of family.

e. Solitude: for the world’s growing number of single-person households, for those whose families do not provide comfort or company, for those who find themselves far from their homes, others?

       3. The Family

a. Rethinking, re-feeling the importance of one’s nuclear family, if there is one, or of having one if you don’t, versus the oppressive feeling of being unable to physically break away from it.

b. Need for keeping close to other humans, versus benefits of social distance, overdose of proximity.

c. Baby boom with welcome/unwanted newborns, versus huge wave of abortions with related political/social conflict.

d. The elderly – their important role in one’s life, their importance and contribution versus the price one pays for their well-being, alternative modes of communication.

e. Violence within the family – rapid escalation following weeks of lockdown, versus exposure of the problem and large-scale treatment by society.

f. Children-parents’ relationship: parents discover their kids who discover their parents and love it, versus same and can’t stand it.

g. What have children learned from the crisis? About their parents’ ability to control their reality, about their family, about the importance of schools, friends, hobbies, or lack thereof.

h. Opportunity for adopting and accepting alternative family models (non-traditional, non-nuclear) by understanding the huge importance of belonging to a community, versus hunkering back to the traditional model of the nuclear family?

B. The Collective

       1. Society

a. The huge inequality challenge: the virus as universal equalizer (“does not discriminate by race or social status”), versus dramatic disparity in rates of illness and mortality along social and economic lines.

b. Realization that the well being of any member of society can strongly affect that of others, that social phenomena can become literally viral, can lead either to a strengthened sense of mutual responsibility towards all parts of society, or to even stronger separation and walling-in of the well off, as they separate and protect themselves from the masses.

c. Coming together or breaking further apart? Expressions and acts of solidarity with those regions or segments of society most affected by the illness, versus isolationist tendencies and blaming of the “other”.

d. Gender: reversal to traditional women’s role in the home accompanied by widespread violence in the family, versus full-time male presence and egalitarian sharing of all family tasks.

e. Gender: Men as weak sex, higher probability of infection, more liable to die, gap in average longevity grows in favor of women.

f. Gender: #MeToo post-CV: losing steam as humanity deals with a host of survival issues, versus returns with vigor, fueled by pressure cooker of quarantines and crisis.

g. Societies with high Gini Coefficients find that a crisis strains the fault lines, bringing to the fore suggestions like universal basic incomes on one hand, versus a reflex of the rich to prepare and protect themselves for future adversity.

       2. Education

a. The role of the kindergarten. Massive realization of the crucial importance of this less prestigious and less budgeted step in the educational ladder, versus experiencing the huge advantage of young children’s spending many hours with their parents and siblings.

b. Homeschooling: the new wave or backlash. Waiting anxiously to re-deposit the kids into educational institutions, versus realizing that having them at home and spending time with them can be an enriching and feasible model for many.

c. Higher education: years of slow ascendance of MOOCs and other online courses accelerated to near-universal adoption of remote learning models vs. finer identification of those aspects that do require person-to-person interactions.

d. General reconsideration of the principal roles of education: transference of knowledge that is deemed important, creating good citizens or enabling individual development (as per Zvi Lam) – when education is decentralized to families.

e. Accelerating (finally) remote digital learning: leveling the playing field through more egalitarian digital education, versus a widening gap driven by high-cost superior digital content and platforms.

f. Opportunity to (finally) adapt pedagogy to technology. When teachers have no choice but to teach remotely, they are forced to adapt their pedagogy rather than falling back on traditional methods and skills, versus total collapse in pedagogy as traditional teachers give up and leave education totally to kids and their families.

g. Will disparity rise when/if a bigger part of education happens at home? Difference in parents’ ability to support home education can lead to focus on parent education, or extra support to counterbalance this effect, or it can lead to widening of the gap.

h. Widespread adoption of the flipped classroom model? Alternative model vying for widespread adoption for the past ~15 years, requires strong abilities of learning at home utilizing digital resources.

i. Education will be perceived by governments as a tool for creating obedient citizens for the next crisis, and therefore will receive extra budget and (at times repressive) attention, versus governments will prefer less educated populations, easier to control in times of crisis.

       3. Communications

a. Role of social media explodes as the only option for maintaining social proximity while socially distancing, increasing the number of people for whom a “friend” is someone you exchange written messages with, and a “meeting” is virtual. Or, social media is mentally associated with lockdown and crisis, driving traumatized users to search for real-life contact.

b. Fake news vs. facts: establishing standards. It is no longer a game; fake news can kill you. Therefore, standards must be established. Versus, no one believes in anyone any longer – there can be no standards since there are no agreed upon experts.

c. Solitude. With technology, even when alone, we are not alone if we can communicate at a distance. Communication has always been crucial, but this has never been so evident. But for some, long stretches of lonely existence revealed how over-saturated they usually are, and how stress decreases when they are less communicated.

d. Decline of face to face interactions versus rebound and consciousness of how much we all need them

e. Growth and importance of independent (from government and business) media. Strong incentive to create and sustain independent outlets but, in parallel, stronger intervention of governments in setting media agenda and controlling media.

f. Digital media thrives as bored viewers are glued to the various screens, increasing exposure to advertising of all kinds, printed media on one hand has increased attention and demand, and on the other hand starved of advertising (plus dealing with logistics and distribution challenges) turns to digital or closes. Will a new model emerge, that can save print?

       4. Government

a. Failure of democracies and advantages of authoritarian regimes in managing crisis situations and enforcing compliance versus failures of totalitarian systems due to lack of transparency, lack of initiative. Jury still out.

b. Local versus national. Only strong central government can deal with magnitude of crisis, versus local leaders and communities taking independent steps as required by their specific conditions.

c. Leadership and lack thereof: rise of the need for strong leaders vs. obvious weakness of relying on the wrong “pseudo strong” ones.

d. Alternative leadership roles: leadership vacuum creates need and opportunity for non-official or non-elected-officials to become the leading voices, or military figures to impose restrictions justified by “emergency measures”.

e. Balance between technocrats and politicians: strong need for politicians to closely consult with professionals on topics in which they have no idea, versus inaction due to endless discussions between experts and lack of authoritative professional answers.

f. Elections by digital platforms become necessary to avoid congregation, but fear of vulnerability and possible interference increases

g. Opportunity for autocrats to dismantle democratic norms and institutions vs. democratic popular backlash through digital platforms and “socially-spaced demonstrations”.

h. Governments’ responsibility to create safety nets for their citizens and population in general becomes obvious (even to “small government faithful”), versus individuals understanding that they can trust only themselves to prepare for next crisis.

i. Who do taxes belong to? Huge unprecedented spend of public money by governments with no clear source of funding, versus fear that this centrally directed spend will allocate resources unjustly and inefficiently

j. Governments must assume responsibility for well-being of immigrants, refugees and itinerant populations out of self-defense, versus migrant populations bearing the price of being away from home and family, and lacking support fro their host governments.

k. Smart cities – huge opportunity to build on existing infrastructures and accelerate development because of need for surveillance and tracking compliance, versus strong backlash due to privacy concerns.

l. Lockdown enforcement creates precedents of mass control over public behavior, especially in cities, versus shift of population back to villages and the country where isolation is easier and more convenient.

       5. Religion/Spirituality

a. Role of faith for people dealing with crisis: huge win of science over religion for many, versus many others who find fortitude precisely in their faith and religious leaders.

b. Decision makers interact with scientists and rely only on data and hard facts, or realize the comprehensive nature of a crisis and carve a space for spiritual and religious leaders.

c. Role of moral leadership in determining strategy: place around the decision making table, versus support for their followers in reality that is a given.

d. Widespread belief in religious or spiritual interpretations of the pandemic (“God’s punishment for our sins” etc.), versus a division of labor between science as explanation and religion/spirituality as guides to behavior.

e. Moral reckoning driving people to organized religion, versus disappointment with minor role of religious establishment in preventing current sorry global state of affairs (pre-COVID).

       6. The Arts

a. Halls and museums will fill up with thirsty art lovers kept away for a long time, versus persistent fear of agglomerations.

b. Public discovers that art can also be consumed from afar, leading to increased appreciation and interest in visiting museums and concert halls, versus leading to lazier habits of art-couch-potatoes.

c. Artists, musicians, dancers have all performed for us at home, many for free, and whetted our appetite to see them live once we can, expanded our horizons and made us better audiences, versus, we are spoiled now and want it for free and on the couch.

d. Variety of models for monetizing art emerge, as desperate artists find way to live from their art in the absence of live events, versus artists give up and find employment in other professions.

e. Collaborative art, facilitated by digital sharing, emerges as the new 21st century medium, or disappears as a fad post-CV.

f. Cross cultural art, free of geographic constraints, grows in importance as part of globalization, versus art follows xenophobic and nationalistic tendencies.

g. Free time at home serves as major opportunity for exposure to art, thus expanding the “base” of art-lovers, versus masses opt for low brow and less demanding activities in their CV-home-hours.

h. Future of museums and concert halls: adapting their physical spaces and installations to pandemic and post-pandemic requirements, versus expanding their strategies to reaching out and distance engagement with their publics.

i. Artists retreat into survival mode, versus celebrity artists follow Cardi B’s (and others’) example to take a strong stance in front of their followers.

       7. Travel and Tourism

a. Visiting other countries will have lost part of its charm for some, but perhaps become a lifeline for the more claustrophobically-inclined.

b. Return in droves to beloved patterns of travel after lifting of bans, versus appearance of new models of tourism (socially-distanced? More local? Remote and isolated? Ecological?)

c. Technological solutions as enablers of travel: screening travelers for fever, filtering and protection in flights and other confined spaces, navigation and translation to minimize contact with strangers, etc. versus technology as a replacement for physical travel, as in VR and AR tours.

d. Post Corona border control using a variety of technologies to enable or restrict travel, by scanning, comparing data to data bases, identifying travelers’ conditions and more.

e. The future of Airbnb – crash as travel contracts, as does trust in the cleanliness and safety of private homes, versus rebound as the company adapts to new realities with novel measures.

f. Tourists prefer sea and sun tourism, away from the masses, versus tourists flock back to cities, thirsty for human contact.

g. Airplanes taking off dangerously after being grounded for weeks or months, versus fleets in best shape ever due to planes finally resting and receiving plenty of maintenance and attention.

h. Importance of hygiene on planes, passengers avoid confined cabins, preference for private flights.

C. Health, Science, Technology

       1. Public Health

a. Discovery of fault lines: weakness emerges in supposedly robust health systems. Low correlation between national health expenditure and readiness of countries to confront the pandemic

b. Strong drive for change of a health system that is perceived as having failed in its main role, versus glorification of the health system that saved us all.

c. Gearing up for new strains and mutations: focus on solving the immediate legacy of CV-19 and its aftermath, versus searching for a universal solution to all future types of virus.

d. Change of priorities: investing heavily in hitherto impoverished national health systems, versus changing the paradigm and rethinking the entire model.

e. Recovering from damage wrought by distancing strategy: keeping the social-distance mentality with a stepwise approach to relaxing constraints, versus identifying the perils of distancing and finding ways to be safely together.

f. Immunization and vaccines: huge emphasis on search for an ever-expanding arsenal of vaccines, versus opting for alternative strategies to combat illness, given the obvious limitations of the vaccine strategy for influenzas.

g. Resource allocation: dramatic increase in budgets for public health, versus widening the gap between poor public services with a parallel system for the wealthy.

h. Scenario planning: strengthening and reopening of forecasting and preparedness units vs. perception that it is impossible to predict so better focus on generic preparations.

i. COVID-19 as “dry run”” for catastrophic scenarios: pandemics of a global scale and grave risks have occurred on average every 300-400 years, so the probability of another one soon is low, versus this was just a mild version of what we can soon expect to be hit by.

j. The ascendance of telemedicine. Necessity has proven that telemedicine is far more effective and accessible than anyone predicted, leading to rapid acceleration of the genre, versus CV exposing the dire need of personal and close primary care to maintain health and thus protect the population from future pandemics.

k. Importance of digital health: the huge importance of data, its analysis, translation into insights and rapid deployment of conclusions, versus the limitations of too much data leading to inconclusive or multiple recommendations and therefore paralysis.

       2. Science

a. In the COVID global theater, science plays lead role of savior, only carrier of hope to billions, and is vindicated as the exclusive approach to dealing with any important challenge, versus powerful pull of religion and spiritual beliefs as only answer in a world devoid of certainties of any kind.

b. The sight of scores of highly esteemed scientists viciously disagreeing on what feels like hard facts erodes the credibility of science as arbiter of truth.

c. Science is fully harnessed to practical purposes, further strengthening the tendency to prefer applied science over theory, versus deep understanding that underlying basic science and theory are the basis of all the anti-COVID wizardry.

d. Countries find that organizing their efforts to confront the crisis requires a cross-disciplinary approach, as do scientists in search of cure or vaccine. Silos, once broken, will remain porous, versus a tendency, as problems become more complex and the need to solve them more acute, to specialize in ever narrower mini-fields enabling an even deeper understanding of limited phenomena.

e. Role of data as a leading tool in the process of science, often replacing the need for “wet” science, serving both as creator of hypotheses and their confirmation or refutation, versus anecdotal evidence that the clinician or experimenter in the field is privy to certain types of insight that the “cold numbers” will never reveal.

f. Even as huge collaborative data-driven science is being performed, a rise in the importance of good old observation, with scientific insights stemming from anecdotal clinical evidence accumulating in real time.

g. Enthusiastic embrace of cross and multi-country collaboration with science as the universal language of truth, versus enhanced competition between countries and realization that only few countries have the budgets and resources to conduct state-of-the-art research.

h. Cuts in funding for science and research as part of general tightening of budgets, versus increase in scientific spending as only defense against future pandemics and catastrophes.

       3. Technology

a. Accelerated pace of technological development was already a cliché pre-COVID, but the dramatic need for immediate solutions, expressed in the towering price, both human and financial, of every day of delay, have pushed technology to hyper-agile tactics, even in traditionally cautious fields such as medical devices and pharma.

b. In parallel to the hubris brought on by a truly overwhelming display of technological prowess, humanity discovers the limits of its power in confronting nature. Specifically, Silicon Valley, the standard bearer of technologic dominance, disappoints in its inability to contribute much to crucial issues.

c. New synergies discovered and collaborations forged between experts in medical devices, various branches of drug development, public health specialists, physicists, computer scientists, mathematicians and others will evolve and expand, accelerating the trend for creating multi-disciplinary labs, projects and companies.

d. Regulation rises to the occasion, relaxes constraints and enables accelerated development, learning that it is possible and opening doors that will be hard to close in the future, versus regulation learns its lesson the hard way after irresponsibly relaxing in its role as gatekeeper resulting in faulty equipment, errors in tests and raising of unrealistic expectations for cures.

e. Technologies at the service of human and social control proliferate, for detecting, monitoring, controlling, nudging, tracking and analyzing behaviors, are accelerating ever more, while raising and confirming concerns over privacy and disregard for human rights.

f. A host of technological enablers of digital transformation, seen pre-COVID as promising but still out of reach, thrusted into public consciousness as they are harnessed for anti-COVID purposes.

       4. Data

a. Dramatically ubiquitous, from popular media to sophisticated algorithms, nobody will ever doubt its importance, versus backlash that human phenomena, feelings, well being are irreducible to numbers and therefore data-based decisions should be limited in certain crucial domains

b. Data is a resource that grows in value when shared, and therefore huge push to share one’s data, versus data as scarce and most valuable of resources, and therefore tendency to greedily hoard it.

c. Citizens have become aware of the amount of data that governments possess relating to them. The good news: they are being listened to, their needs can be analyzed and treated, solutions can be customized. The frightening news: all the above can be converted to control and suppress.

d. New models emerge for sharing and ownership of data to allow both sharing and monetizing.

e. Crucial role of data in decision making: leaders realize that they need a dashboard of data to reach rational decisions, but the predominance of certain types of data (number of ill, number of dead) in public discourse also skews decisions towards simplistic approaches (e.g. decrease number of COVID casualties at the price of disregarding all other casualties and costs).

f. As the world’s reliance increases, so does the importance of mechanisms to validate their source, integrity and precision, but as the barriers to publish data diminish so does its fidelity.

D. The Globe, the Planet

       1. Sustainability

a. COVID provided a demo of the planet resting, air quality, animals resurging – maybe this experience will make it harder to fall back to our old polluting ways?

b. An opportunity for global collaboration to save ourselves by slowing down the pace, versus each country frantically throwing itself back into the race to make up for lost time compared to others.

c. Can the world agree on Global Sabbaths? We saw that we can withstand weeks of time-out and even enjoy some of the consequences, so can we decide on a day per week? A week per year?

d. Heightened consciousness of the situation given the dramatic impact of the global pause, and therefore: Opportunity for a Global Green New Deal? Or backlash to put aside sustainability in favor of “more pressing” issues?

e. Remember that while we humans put ourselves on pause for the CV, global warming and related negative phenomena have (mostly) continued. Will this serve as an argument for or against human made global warming?

       2. Global Politics

a. Humanity has finally united against a common, non-human enemy, and, realizing the huge potential of this unity, organizes itself to deal with the major global issues?

b. Nationalism and racism are further stoked by autocrats and shamed governments in search of scapegoats, while opportunities for “catastrophe diplomacy” abound, as traditional enemies express their solidarity sending materials and volunteers or sharing crucial information.

c. Xenophobia arises from fear of the other, the foreigner: “the virus” will always arrive from the outside, confirming deep seated fears of those who “don’t really belong here”, or “eat weird stuff”, etc.

d. New global organizations will be founded and existing ones strengthened as countries understand their crucial importance in defeating enemies that transcend borders, versus fatal weakening of global organizations as a chain effect of the US pulling out, cancelling its contribution to the WHO, blaming these organizations for the initial failure of global response to COVID.

e. As the role of data both increases and becomes more evident, and in parallel the most important challenges are recognized to be global, the need for a data sharing on a global scale is inescapable. The world creates the United Nations for Data.

f. Tectonic shifts among world’s superpowers: the US continues its decline, or proves its strength in rebounding and supplying the (bio?)technological solutions to the pandemic; Russia hit hard by plummeting petrol prices combined with what seems like inadequate and totally opaque treatment of the crisis; other BRICS in general in bad shape; EU while dealing with Brexit exposed as the elderly inefficient continent (in the south) or a model safety network for post-capitalism (in the north).

g. As traditional wars are put on pause, the rise of soft power in international relationship, expressed not in tanks and warships but through scientific, industrial and social strengths vs. rapid re-flame of numerous local and regional wars and fighting.

h. Increase in power of China and Asia, the “winners” of the crisis, vs. shrinking export from China and Asia due to CV trauma in rest of world

       3. Global Economy

a. As countries and peoples realize that GDP does not ensure real prosperity, an opportunity arises to break away from GDP as the god of indicators, replacing it with more subtle and complex measures that capture well-being and are therefore better guides for national strategies.

b. What will happen with the huge and growing debts of governments, businesses and individuals?

c. Widening of the inequality gap between countries (those who won from the crisis vs. those who lost), or the crisis as equalizer, where giants fall to their knees and smaller, poorer countries forge ahead with minor injuries?

d. Trigger to scale down globalization, the great pandemic accelerator, versus opportunity to create a more fair, transparent, equitable model of globalization, increasing collaboration and interdependence.

e. Will international alliances and organizations impose criteria about readiness for crisis on their members?

f. Huge government bailouts: exacerbating inequality (taxpayers funding corporates), versus fairer models in which taxpayers share rewards of the bailouts as well as their risks.

g. Unprecedented stock and commodity market volatility leading to strong disillusionment with current investment mechanisms and corresponding losses as the public’s money flees to safer options, versus opportunity for even bigger gain for a connected minuscule minority.

E. Work, Business

       1. Work, employment

a. Working from home, now proven to be effective, becomes widespread, versus emphasis on all we couldn’t achieve without physical presence will strengthen demand to be present. Will hybrid models proliferate?

b. Influence on home/office design and therefore on real estate?. Will offices become smaller and homes larger? Will this affect prices? Locations? Architecture?

c. Workplaces hygiene will become a dominant concern, versus the apparition of a “magic chemical” that will make efforts to maintain hygiene appear quaint in retrospect.

d. IT becomes even more important than it is today. It converts into your partner, holding your hand for all your remote activities. Dependence on IT grows – the worst thing that can happen to an employee is to be left without a connection.

e. The gig economy – exponential growth of the perfect format for digital experts, deliveries, nomads, minimizing proximity to co-workers, services for lockdown, outsourcing for cash deprived businesses, only solution for many employed and more.

f. The gig economy – dramatic weakening: fear of proximity to variety of strangers (Uber, AirBnB), workers yearning for the safety of a salary, pensions, safety net.

g. A great gap between how “essential” a worker is considered and how much they are being paid. Will essential workers be able to leverage the crisis to improve their lot, or will society search for and find ways to continue their exploitation?

       2. Business: General

a. Values: a tremendous opportunity for businesses to live up to and showcase their values, accumulating loyalty points in the eyes of customers and prospects, versus moment of truth when values are shelved in favor of cost cutting and survival mode.

b. Recovery from the crisis. Most businesses will bounce back rapidly thanks to: pent up consumer demand, loans and grants injected by governments, benefits of low oil prices, accelerated COVID and health related activity, large government projects and contracts, or: Catastrophic slow recovery due to: huge debt, businesses who failed to survive the lockdown, furloughs converted into unemployed, unemployed failing to rejoin workforce, chain effect of businesses hit by low oil, inconsistent and insufficient governmental recovery plans, deflationary effects of uncertainty and fear.

c. Emerging and declining businesses (winners and losers from the crisis). Obvious winners and losers from lockdown: hand sanitizers, Zooms, take-aways, Netflixes, healthcare, analytics for the former; airlines, tourism, car makers, art industry in the latter. But, also, suppliers of the abovementioned and others influenced indirectly. In some of these “losing” categories, survivors may surprisingly end up way ahead of their pre-pandemic position thanks to the disappearance of competitors who did not survive COVID-death valley.

d. New and old competitors: united against the common enemy, companies frantically and generously opened their knowledge and markets to newcomers in order to jointly supply, say, masks or respirators, which may lead to a beautiful future of collaboration, or, to a fight to the death with newcomer competitors.

       3. Retail

a. Buyers’ behavior post weeks/months of remote buying and limited budgets (for the majority): trend towards buying less, sticking to the necessary, versus hoarding mentality to prepare for any eventuality.

b. Limited movement drives shoppers back to small shops close to home, or strengthens large retail outlets that can offer and deliver bulk discounts.

c. Barriers broken for the pre-CV non-digital-savvy, leading to dramatically increased share of online shopping, or nostalgic impulse to return to the “good old shops” pre-CV.

d. Shopping centers, malls – will they survive the need for social distancing even months after the first wave abates? Will they evolve, in terms of interior design? Opening hours? Activities for shoppers (to keep them from running back home quickly)? Hybrid models of collaboration with digital channels?

e. Shops and independent retailers animated by close to home shopping, versus massive closures due to cash flow, loans, competition from large players?

f. New models of retail will sprout and grow, such as smart subscription retail (for those who can afford it), while the trend for locally sourced produce increases because of distrust of the far and foreign.

       4. Supply chains

a. Push for cost saving and efficiency leads to leaner distribution structures, while worries about maintaining supplies in times of crisis drive preference for distributed supply chains, with hubs nearer to end users.

b. Strong push for 3D printing and on-site manufacturing or last mile assembly to skip steps in distribution, versus recognition of the limitations of these technologies.

c. Manufacturers will put a premium on old and trusted relationship with suppliers, who can be trusted to deliver under any conditions, or widespread search for alternative suppliers, and the safer redundancy of multiple suppliers.

d. Companies opting for large inventories vs. just-in-time with close-by reliable suppliers.

e. As commercial flights and other means of transportation are prohibited, their providers close and/or their prices rise, alternative options for delivery will appear: drones, finally?

f. The benefits of globalized supply chains have been emphasized by their absence, but so have the dangers of relying on them. As local governments invoke various versions of the “Defense Production Act”, will globalization continue or will there be increased focus on localization and supply chain continuity?

       5. Transportation

a. Public transportation in pandemic times: increase in usage with alternative models, hygiene and spacing of passengers, versus decrease in usage per limited movement in public.

b. Rebound for autonomous shared vehicles, as users prefer to avoid proximity to drivers, vs. preference for own cars, with full control of access to strangers.

c. Uber and shared rides: surge as people avoid mass transport, versus crash as gig drivers without safety nets go bust vs. shift to drivers as employees

d. Strong adoption of alternative non-polluting fuels following rising consciousness of the damaging effects of oil-based, vs. return to oil guzzling habits due to record low prices.

       6. Manufacturing

a. Increased automation to minimize dependence on virus-sensitive humans vs. increased use of humans for remote operation of manufacturing equipment.

b. Versatility – proven ability to switch to manufacturing totally different products in crisis mode may lead to adoption of this flexibility in commercial contexts.

c. On-shoring backlash to off-shoring trend driven by: governments’ efforts to “bring back jobs”, fear of geographically long supply chains and increased automation.

d. Focus on redesign of plants for distancing and hygiene? And/or emphasis on workers’ well-being and health? Voluntary or driven by legislation?

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