“The reality is that many or even most business leaders made choices over the past decades that traded resilience for a perceived increase in shareholder value. Now may be the moment to consider that the era of chipping away at organizational resilience in the name of greater efficiency may have reached its limits. This is not to say that there are no efficiencies to be sought or found, but more that the trade-off between efficiency and resiliency needs to be defined far more clearly than it has been in recent years.

McKinsey & Company

Resilience is the ability to bounce back – to quickly adapt to major disruptions and crises while maintaining business operations and substantially preserving people and assets. It involves absorbing stresses of many kinds, recovering in a timely manner, and even thriving creatively in the new situation.

Almost every business has some degree of resilience. Every business encounters major headwinds and challenges and, to the extent that it survives, it is resilient.

Being “slightly resilient” is probably good enough to carry a business through the normal series of ups and downs but only the strongest (or most fortunate) will make it through the big hits – such as we have today – without serious damage.

Measuring resilience

How exactly do you measure resilience in a way that allows you to take actions to improve your resilience and to track the results? How much resilience do you need? Is there such a thing as “over-resilience”?

While there are many actions a business might take to improve resilience, the nature, extent, and duration will depend on what you are trying to achieve.

Decreasing debt and increasing cash will certainly make you more resilient but just what debt and cash levels are required for resilience? Should you try to prepare for a catastrophic hurricane, or maybe a major war, or even a big earthquake? What resources are you willing to dedicate to improving resilience?

Redundant or cloud-based information systems improve your resilience in this dimension but what about the dozens of other business factors? A big hit can mess up a lot of things, technically speaking.

Are there any broad measures available that might help us here?

A proxy for resilience: Altman’s Z-Score

Business stress shows up fairly quickly in its financial situation. Developed in 1968 by Edward I. Altman, a professor emeritus of Finance at New York University’s Stern School of Business, the “Z-Score” was intended to predict the probability of corporate bankruptcy. Z-Score is high if it has demonstrated an ability to grow relative margins (as measured by EBIT/assets) while increasing relative revenues (revenue/assets) and maintaining a strong financial cushion (retained earnings/assets). Lower Z-Scores indicate higher stress.

The McKinsey article (linked above) tested 1,300 companies for stress level changes over the 2019-2020 period and found that 25% moved to higher stress levels while just 3% saw reduced stress.

There are probably only a handful of fortunate businesses today that are not feeling extremely stressed by what has happened since March 2020. An ability to see ahead and plan for overcoming obstacles is what helps a business deal effectively with stress.

Planning for the unimaginable

But how can you plan for something that you cannot foresee or even imagine? I wrote a while back about black swans, which thanks to Nassim Taleb, are the current icon for such happenings. From this post:

“You all know that a “black swan” is an event or situation that was not and could not be foreseen. Unpredictable, extremely rare, severe impact. When all bets are off, as they say. Times of great change seem to attract black swans. We are in black swan days today.

So how can you adapt to something that cannot be foreseen, may never happen until it (whatever it is) does happen, which then makes an incredible mess of things?

The answer seems to be that you need to maintain a high degree of flexibility and diversity, especially during such times. You have to build this capability set into your business before you get ambushed by a black swan. But, since we have already experienced our black swan day, we really don’t have to be concerned about more black swans, do we? You wish.”

The year 2020 has been a poster-child black swan happening. A sequence of events and responses so improbable that even sci-fi would have rejected them in past. Sure glad 2020 is over, yes?

Not so fast:

Black swans hardly ever travel alone.

A “black swan” – a rare, high-impact, unexpected, unforeseeable event – is something that you can’t plan for. You have no idea beforehand as to what it might be or what impact it might have. All you know is that black swan events do occur. An event that was foreseen, even if not fully, is not a black swan. It is simply life.

Black swans are distinguished by our lack of ability to foresee them. If we can foresee an event, it is not a black swan.

The Galveston TX hurricane storm of 1900 that killed thousands was a black swan at that time. Today, we can track such storms well ahead of impact and even get a pretty good handle on impact severity. They are no longer black swans.

Despite COVID-19 being labelled by some as a “plandemic”, it was not foreseen (except maybe by mysterious planners) and its impact was beyond huge in terms of the government response and population fear generation. It is a black swan for all practical purposes. And it is almost certainly just an initial hit.

The honking of a black swan flock is beginning to get louder. The 2020 elections have morphed into a catastrophe almost no matter how the results turn out. Assuming that they ever turn out. The election mess was certainly foreseen in general terms as a possibility but not as a likely happening. A big meteor hit is a certainty but timing and magnitude are unforeseeable.

Like me, you may well be wondering: “What next?”.

Photo by Liu Yuting on Unsplash

“What next” is surely on the way

We are certain to be hit a series of “somethings”, big and small, in the future. Always have been, always will be. Probability 100%.

The real question is what should we do to prepare as best we can for whatever comes along next. No specific event in mind: we just want to be more hit-proof.

Clearly, the answer is to address as many impact-vulnerable areas of the business as we can. Concentrations of sales among customers is a serious vulnerability. Concentrations of sales among products is also risky. Facilities located in high-risk regions may need to be relocated or mirrored. The list here is long.

Larger organizations can carry out pretty detailed analyses of vulnerabilities, impacts, and possible responses for protecting. This takes time and considerable resources that may no longer be readily available. Is there an alternative, simpler, faster approach that almost any organization can use?

Well, yes there is – at least in principle.

Business dynamics simulations

This is a specialized field of computer modeling – simulations – of complex dynamic systems, such as businesses, for the purpose of testing holistically the effects of different sets of management actions under a range of possible business scenarios.

MIT’s John Sterman in 2000 published perhaps the definitive reference on this topic: ‘Business Dynamics: Systems thinking and modeling for a complex world. McGraw Hill”. There are a number of excellent software packages for systems dynamics modeling, including ithink, Powersim, and Vensim. Wikipedia has a comprehensive list.

This approach is especially powerful but not commonly used so far as I have been able to determine. Consultants such as London/New York-based The Berkeley Partnership offer such services but the majority of consultants seem to be mostly tool builders and academics.

In practice, this is pretty complex stuff. Models are typically hard to develop and even harder to validate.

Is there a practical solution here?

Yes, I believe so. I am at this interesting moment in our times working on just such a critter. Technically speaking.

The approach in outline is this. You build a relatively simple model using data and parameters that a business can actually measure. This turns out to be a standard set of financials plus a number of driving parameters that are determined from actual business data. The real challenge is making such a model dynamic in a realistic manner.

This requires some mechanics for translating likely management actions into business financial responses to a range of possible scenarios. Below are three test scenarios that the current model version indicates will lead to business failures in each case assuming business-as-usual management practices.

The challenge presented here is to identify a set of actions that can prevent the failure (typically bankruptcy). Examples include: reducing staffing wherever feasible; selling receivables; stretching payables; reducing inventories to reflect lower sales. Obvious business responses but very tricky to model.

Three model test sales scenarios

This is a work in progress that will require another post to explain in more detail.

Application to your business

The concept here is to build a properly structured and parameterized model based on your business and then to test a range of real management actions against a set of sales scenarios to see what the model response might be.

Model output would then be compared to actual business performance and management actions in order to refine both the model and the set of working scenarios.

This is in effect fitting the model and its dynamics to the actual path of your business and its environment.

Achieving greater business resilience

You will certainly see that the evolving model can be used also to test its response to various external situations that might occur. This should illuminate areas of particular vulnerability and help aim your resilience-building efforts to where they are likely to be most productive.

Bottom line:

Does this idea make sense to you? I’d very much appreciate any comments that you may care to offer.

To be continued in a future post.

McKinsey & Company seems to have an especially broad and excellent set of articles on the general topic of resilience. Some examples:

“Meeting the future: Dynamic risk management for uncertain times”

“When nothing is normal: Managing in extreme uncertainty”

“The emerging resilients: Achieving ‘escape velocity’”

“Risk, resilience, and rebalancing in global value chains”

“How retailers can build resilience ahead of a recession”

The U.S. Chamber of Commerce Foundation offers a number of specific suggestions about improving resilience in its “Business Resilience 101 Workbook”:

“Resilience in a Box is based on best practices and is designed to educate newcomers on Business Resilience. Small businesses are both highly vulnerable and without adequate resources with which to focus on taking preparedness actions. These resources will guide your company toward addressing preparedness issues while building in the flexibility to handle potential business interruptions. Resilience in a Box consists of 3 elements:

1. Tools

2. Training

3. Resources

“Resilience in a Box tools are designed to lead every business—even one with no disaster experience or understanding–towards improved resilience. The tools were developed with three levels: Basic, Intermediate, and Advanced. The Intermediate level builds upon the Basic tools in order to get businesses better informed and able to readily determine specific actions that will enhance their resilience against all hazards and potential interruptions. The Business Disaster Resilience 101 Workbook (101 Workbook) is an Intermediate level tool as it provides more detailed business readiness guidance, tips, and resources to assist companies by addressing their own assets before a disaster occurs.”

Gerry Allan’s doctoral thesis at the Harvard Business School was: “Competitive Behavior and Corporate Growth (1978)”. It involved developing and testing a somewhat complex systems model of the major chemicals industry (e.g., Dow, DuPont) and its rules for deciding on capital investment and other top-level business factors.

One unexpected finding is that the model predicted failure (i.e., most industry players went bankrupt) except for a quite narrow and specific set of decision rules. Under these particular rules, the industry was stable and thriving under a wide range of external conditions. It was the decision rules, not the misbehaving real world, that determined success or failure.

Business resilience involves discovering and implementing the strongest set of management decision rules and practices for a particular business.