Thank you for subscribing and being part of this community. The likes have significantly increased on some post series, which helps me a lot. I know more about your interests and, more importantly, what isn’t interesting. I’ll be ending series that prove to be unpopular to focus on those with the highest interest. You are helping me focus on value which I sincerely appreciate.

I talk confidently about the future, and my confidence is information driven. The data, my conversations with others, listening to experts, tracking connected domains, and reading research all contribute to my view on what’s next. I work to convince myself before sharing my opinions publicly.

Does that mean I’m always right? Of course not. The future is not fixed, and no one can consistently predict the details of what comes next. The bigger picture and some high-level constructs are more consistently predictable.

I called a coming 12-18 month slowdown back in February when most people had yet to acknowledge there would be a slowdown. Now that range is well accepted. I said it would probably start in summer or fall 2022. That was a stretch, but it looks like I got lucky. It was hard to say it in public then because uncertainty ruled.

I had the data, expert agreement, and c-suite confirmation. What’s the point of gathering all that if not to make a prediction? The fear of being wrong keeps many data scientists from presenting their findings.

What I had would not hold up to scientific review. It was insufficient to call rigorous proof. In poker, what I did was the equivalent of pushing all in when there’s a royal flush draw on the table, but I have the next highest possible hand. Yes, I may be wrong, but I can’t base decisions on fear and uncertainty. I must have confidence in my information to act on it.

If I don’t, how can I expect anyone else to? My job is deeply rooted in risk management, which requires taking risks. I help clients take intelligent risks. I also build mitigation strategies or contingency plans in place to reduce the impacts of being wrong.

Risk and uncertainty drain our motivation because there is risk in doing anything. Contemplating an action forces us to confront the risk landscape. If we do anything, the risks fly into our consciousness. It can feel like the best course of action is no action.

That too presents risks, but they are easier to ignore. Making no prediction about a coming downturn eliminates my chance of being wrong on the surface. In reality, my content would be inaccurate. I would continue to explain the as is reality. People would act on my content and run face-first into a downturn.

For example, if I don’t look forward, I would advise people to avoid taking any new job where stock is part of the total compensation package. That would align with the tech sector tanking, where many people’s stock options are deep underwater.

However, looking forward, I know the economy will rebound, and stock options issued at today’s share prices could be worth twice what they are now in 2025, just after they start vesting. Now is a great time to take stock from a stable company with free cash flow, competent leadership, competitive advantages around its core business, and a long-term growth vision.

There is peril in my advice. The downturn has some chance of being prolonged and deeper than I expect it to be. I am concerned about this scenario and called it out in one of my prior posts. I have built monitoring dashboards and mitigation plans for clients around a prolonged downturn.

Here’s my thesis, the risks, next most likely alternate possibilities, my recommendations, and risk mitigation strategy. Data science and a research-based approach help us to act when it’s easier not to, but essential to maintain success.

In the current economy’s rampant uncertainty, motivation is hard to find. It is far more comfortable to stand pat and ride this out. Reaction is a more uncomplicated strategy than moving based on the best available information. The businesses that pull back on growth investments and do not pursue new, high-quality opportunities will not survive the rebound.

Look at industry laggards and businesses that went under in the 2012-2016 time range. Many stood in place during the Great Recession, and that decision was strongly linked to their eventual bankruptcy. Amazon and Apple invested into the downturn and came out the other end as titans. Not every play they made worked out, but that risk was well managed.

I started my current business in 2012 when recovery was the most likely scenario, but far from certain. I had a lot of doubters in my first year. If I had waited until the recovery was inevitable and already underway, I would have been just another freshly minted data science shop instead of an established practice as data science boomed.

Risk, information, and motivation are partners in building success. Data scientists are far more valuable in downturns and in times of high uncertainty than we are when everything is easy and predictable. However, we only achieve our potential if we trust our information enough to act on it. We will be wrong, and that will sting our pride. The mitigation strategies will keep us from losing credibility or getting fire altogether.

For us to do anything meaningful, risk will always be a part of our jobs. Success requires us to stay motivated during uncertainty. When everyone else is too scared to move, it’s our job to lead the way.

Vin

High ROI Data Science

Motivated Mondays During Uncertainty