We are awash in talk of data. It has become a truism in the world of business that data is the most valuable resource in the world. Organizations of all sizes are investing in data, data infrastructure, and new uses for streams of data. This has ushered in a new era in which business models are based on “data-plays” and valuations soar if the market recognizes even a modicum of long-term potential. Such scenarios are exciting for many and difficult for others as making sense of the noise becomes increasingly complex. More organizations admit that there’s a wide divergence in their rhetoric about data and their ability to gather, manipulate, and act on data in a timely and comprehensive fashion. We believe this divergence is based not on some fundamental inadequacy but in an error in approach.
Most business leaders suggest that the evolution of their organizations would lead to a culture of data-driven decisions. This is indeed a great goal. Hidden in data are truths that most of us cannot “see” with the “naked eye.” Interestingly, this is true in any discipline within the organization. Salespeople can always use new and different ways of conceptualizing their customers’ buying needs. Marketing can use data to test hypotheses quickly and to alter Marketing campaigns in scale and scope. Product engineering can develop new features and innovate based on data on real use and consumption. Finance can use accounting and operational data to provide resources to different parts of the organization based on agility and time to profit. The list goes on. Yes, a data-driven culture is great.
As with most things, however, its very idealism is also partially its undoing. Precisely because data is so voluminous and so applicable to literally everything in the organization, pin-point clarity is hard to come by. An explosion in variables and inputs creates a massive upswing in complexity. Data points are often not causally related. In such situations, what data does one act upon? What data is relevant? What data is “clean?” How do different data sets conjoin and create a unified narrative? These questions vex all organizations, even the most data-mature.
Clarity can indeed emerge, but the script must be flipped. Instead of a “data-first” methodology, business leaders must determine and then focus on the key decisions that must be made and therefore what data investments to make to support these decisions. Once data projects are anchored by key decisions, then success criteria become grounded in increasing levels of probabilistic causality for more calculated decision making.
Data is indeed life-like water but a deluge of data makes for a water-logged business. Taming the deluge is key. Focusing on key decisions presupposes a clear-cut winnowing process. In this, no doubt, some useful data is thrown out, but without it, data agility is impossible.
Putting decisions at the forefront creates the possibility of a truly decision-driven data culture.
