Knowledge Worker for the Robotic Age: Quantitative Thinking

The impact of robotic process automation, AI, machine learning and cognitive computing will be significant and profound, likely upending the traditional recipe for organizational capability- people, process and technology. The proportion of these ingredients might be re-jiggered to something like technology, process, and people. So, what’s a human to do?

In an earlier article, Five Tool Knowledge Worker for the Robotic Age, I outlined the skillset that I believe will be required for modern knowledge workers to thrive in an environment where robots and automation dominate many roles previously performed by people. The five tools are  quantitative thinking, communication, people centricity, planning/process thinking and critical thinking. In this post, I will delve into the quantitative thinking tool that the modern knowledge worker needs to possess to be successful going forward.

As my kids made their way through advanced math subjects, such as algebra and calculus, they continually asked, “will I use any of this in real life?” The answer is a resounding, “well…kind of…” Being comfortable understanding numbers and processing their implications analytically is a vital tool in your toolbox, because “making the numbers” is an existential imperative for any company to survive, let alone thrive. Below are some aspects of the quantitative thinking skill that are particularly important proficiencies for a knowledge worker :

Business Frameworks– Businesses use a few common frameworks to organize the numbers to understand performance and financial health. The P&L (profit/loss statement), balance sheet and cash flow statement are the fundamental scorecards of the numbers. All other measuring sticks are a drill-down of important parts of the big three. Sales and quotas are concerned with the top-line of the P&L, operating profit is the bottom-line and gross margin is in the middle. Cash, investments, accounts receivable, inventory, etc. populate the assets portion of the balance sheet. Debt, payables, etc. make up the liabilities and stock, retained earnings, etc. make up the equity section. The balance sheet is so-called because this framework of numbers “balance” with assets = (liabilities + equity). It is essential to learn how to read the P&L to understand business performance. You should then move on the balance sheet to get a sense of how your company is using assets and how encumbered you are with debt. The interaction of things on the P&L and balance sheet result in cash flow, which is really the most important thing to an ongoing concern. Cash is king.

Rates of Change – A company’s financial statements tell a story but they are static numbers, at best a snapshot of activity. The real insight comes from how things are changing. This is the realm of percentages. Is revenue (a fancy word for sales) growing? Are expenses going up? If so, how much are they increasing relative to last month, quarter, year? Whenever I hear that sales are down X% somewhere, I think, uh-oh, they’re in trouble. It is very hard to adjust your cost structure fast enough to cope with a shrinking top-line and resulting gross margin loss. Morevoer,  the ways to do it are not pleasant – austerity, layoffs, closings, asset sales, etc. If you’re not growing, you’re dying. Rates of change will tell you which direction you’re headed in and how fast.

Statistics – Statistics can help you understand what’s going on by using a few descriptive numbers calculated from a larger set of data. Get familiar with a couple of statistical terms and concepts like range, mean (aka average) and standard deviation so that you feel comfortable engaging in areas such as product quality, market research and customer satisfaction. If you’ve heard about Six Sigma, then you may know that statistics are the foundation of this discipline. This is where the advanced math learning you received in higher education will come in handy. Luckily, most of the math is done by specialized statistical software these days. After all, robots are very good at math…

Database Thinking – Numbers are pieces of data and can give you greater insight when they are fully described and further processed to tell you more. Organizing numbers to enable “slicing and dicing” and drill-down requires what I call database thinking. Basic database applications such as MS Access and Excel (yes, it can be an effective database for small data sets), want you to organize data into records. One record per line/row (forget the formatting and line spacing) and attach all the relevant attributes across the columns. Taking the time to organize numbers in this way will payoff in a meaningful way with greater insight and the ability to answer today’s and tomorrow’s questions (think pivot-tables). This approach is effective and appropriate for “small data” (up to around 100,000 records) that is ‘clean” and can be structured consistently. With the explosion in the amount of unstructured data being produced/captured today, “Big Data” management and techniques need to take over. Advanced statistical tests and algorithms are needed to mine these data sets. Data and information are sources of great value and competitive advantage, make sure you are literate in this area. Once again,  robots are…

So, those are some aspects of quantitative thinking in which a knowledge worker needs to be fluent  to be able to keep ahead of the robots. Remember, the real power of the five tools comes when they are used situationally and in combination with one another. You’ll be naturally disposed to be better at some than others. Play to your strengths, but keep developing the others as well.

In my next post, I will elaborate on the communication tool for the knowledge worker. I have plenty more blog post material tumbling through my head during my LSD runs (Long Slow Distance, not psychedelics) on the weekends. I will continue to share until the content runs out. Please feel free to contribute your comments and feedback.