When it comes to data analytics it’s not the size of the data that matters, but the quality of the insight and actions you generate from the information available. In the era of category creators like Tesla (0 to 60 mph in 2.5 seconds, in a luxury electric vehicle), UBER (your personal driver) and Big Ass Fans (temperature comfort in large buildings using high volume, low speed fans — HVLS); what really matters is how much granularity and definition you can bring to your product or service portfolio and to your marketing efforts. Everything else is noise and complexity.
Smart analytical companies are increasingly resorting to the empirical and age proven Pareto Principle, aka the 80/20 Rule, to create new insight and value from big data. The inexorability of imbalances in the data and the clear separation between vital few and trivial many are forcing algorithms to learn and to incorporate this familiar experiential model. And it’s no surprise when, time after time, big data analytics keeps pointing to the fact that only a few customers and products explain the majority of margins dollars and growth.
Michael Schrage[1], from MIT Sloan School, writes that Pareto Analysis is getting turbocharged by machine learning algorithms and redefining how organizations perform data analytics. As algorithms get trained (Smart-Paretos), companies can easily and automatically identify key customers and products, transforming “vital vectors of variables into new value”. Second, firms can drill down into new proportions (Super-Paretos) closer to 10/90, 5/50, 2/30, and 1/25. With higher granularity and multiple interrelated data sets, analytical companies create small portfolios of Paretos (Supra-Paretos) to manage complexity, redefining the term KPI to become “Key Pareto Information”.
With extreme data and complex correlations, companies need to use the simpler and reliable Pareto Principle to gain deeper insight. Innovation, product offering, market targeting and simplification need to “be analytically informed by Pareto pathways”. Michael reaffirms my experience, which is: “the smarter your algorithms, the more they — and your organization — need to be learning from and with Pareto”.
The use of Pareto Principle in analytics elicits three other empirical principles that I consider fundamental for entrepreneurship in the era of category creators. Most entrepreneurs apply these four principles deliberately or instinctively. I have myself used these four practical principles to guide my work and personal life.
Pareto thinking (the first principle) leads you to tap on natural imbalances and use them to your favor, allowing to reallocate time, resources and efforts from the trivial many to the vital few, creating leverage. When companies place an ultra high focus on a select group of customers and products, they raise performance significantly. The analytically derived and extremely sharp focus leads to well-defined target markets and customers with very high levels of granularity (the second principle). Having high-definition, highly granular segmentation of a larger market, enables market leadership in a new product or service category. Shortly after Big Ass Fans launched the HVLS ceiling fan category, they had 100% market share. They were alone in this new category and didn’t have to compete with every ceiling fan manufacturer in the world (at least for a good while).
Market niches, customer and product categories are “fractal clusters” within broader markets. There are self-similarities all over the place and the safest way to define the “right” level of granularity for your offering is to use Pareto analytics. Self-similarity confounds the company into thinking that an existing value proposition or business model can work across multiples markets. Only a good set of “Pareto glasses” can cure market myopia and increase portfolio momentum.
Granularity allows deploying innovation effort to a finer segment of the market and its customer’s “pain points” and “jobs to be done”. The sharp focus on the vital few keeps you from wasting money with low value customers and segments. Innovation, the third principle, is the engine that drives evolution. Once smart companies zoom in and understand pains and jobs to be done, they can systematically raise their singularity level in the market. And it’s not all about product innovation. Airbnb is an example of a category creator that innovated to solve problems for travelers who want a different experience when they go on the road. They ask customers “why vacation somewhere when you can live there?”.
The fourth principle is simplification. Smart companies are born simple and kept simple. But complexity has a way to come in uninvited as the business grows. Causing simplicity to happen is the only way to take away complexity. Causative simplicity helps the business thrive and grow through the ups and downs of the economy, by pruning all non-essential costs and activities and leaving only what is meaningful. Separating the vital few from the trivial many is one approach to cause simplicity. And here again KPIs (Key Pareto Indicators) are essential to help detect and get rid of complexity.
Fintech companies are emerging, providing fast and uncomplicated financial services. The unique value proposition is based on simplicity and on taking advantage of the fact that almost everyone has a cell phone and a social network, allowing peer-to-peer lending, money transfers via SMS and other financial transactions using a mobile device. Aside from simplifying life for a segment of the financial market, Fintechs are built to stay lean and simple. They differentiate from each other based on their ability to master Super-Pareto analytics and market to ultra high definition customer segments.
These four empirical principles — Pareto, Granularity, Innovation and Simplicity — are closely connected to each other. They form the basis for modern entrepreneurship and greatly impact the company’s singularity and portfolio momentum. I have no doubt that the new category creators are already applying these purposefully or intuitively. Managers and entrepreneurs need to master the thinking and the tools that go with each one of these principles, if they don’t want to be left in a shrinking market.
[1] Michael Schrage, a research fellow at MIT Sloan School’s Center for Digital Business, is the author of the books Serious Play (HBR Press), Who Do You Want Your Customers to Become? (HBR Press) and The Innovator’s Hypothesis (MIT Press). Article from Harvard Business Review (AI is going to change the 80/20 Rule), from February 28, 2017.
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