Our COO Scot put together some thoughts on organizations’ “data maturity” levels that we think can help organizations assess where they’re really at with data in their decision-making, and understand what it will take to advance how well data is put to use in their organization. Hint: It’s not just about data-tech.
It would be hard to find a manager who would not confirm, if asked, that yes indeed they have a data-driven organization. With the relentless attention to “big data” and “data science” that’s flooded business conversations since the early 2000s, it’s clear that all organizations feel they must have data and use it in their operations.
But there seems to be a difference between having and using data for selected purposes, and being truly “data-driven” in conducting your business.
A truly data-driven organization puts the insights and predictive guidance from analysis ahead of any Sr. Manager’s or Executive’s expert opinion, or strategic intuition, or whatever decision heuristic these senior decision makers use that is based first and foremost on their prior experience and/or present seniority.
But with two decades of data being touted as the fundamental basis for how business decisions should be made — most of us would admit that in many of the organizations we observe, managers are still basing a lot of their decision making on their experience and seniority and the authority that their position confers on them — without always (or often) vetting their beliefs/expectations/intuitions against data that could prove them wrong.
So while all organizations have data they use in some way within their operations, it is likely that not all decisions in all organizations are data-driven. We believe there are two other stages of organizational “maturity” around data that precede becoming data-driven: being data-driving, and being data-centered.
The descriptions below will help you understand which of these three types of organization you are actually working within. If you’re feeling extra data-driven, go take this quick survey first that will give you a type, then read on below for insights into that type.
The Data-Driving Organization
Managers (and/or agency strategy/account folks who serve managers) like to be seen as having earned a strong sense of business savvy through their career. There’s a real thing called “authority bias” that leads people with authority (and people deferential to authority) to believe that being given authority means you’re inherently correct about things more often than other people.
Of course, the reality is that often people in authority are just more politically motivated and good at working in networks. Being good at decisions around consolidating personal power and building alliances does not make one good at decisions that deliver profitable growth to a business.
Strategically effective data-driven organizations hire and promote in a way that gives decision-making authority to people who won’t just trust the insight from their experience — but will actually test and analyze every possible decision with data until they find the one that holds up best in a predictive evaluation of what’s long-term best for the business.
But things are the other way around in data-driving organizations. These organizations are ruled by HiPPOs — the Highest Paid People’s Opinions. In the data-driving organization, the manager’s or expert’s insight about what the right answer is comes first, then data is sought that validates this foregone conclusion. That’s the data-driving force; find data and analysis that makes the manager or expert look smart for the decision they made.
Only after managers have committed themselves to spending on the new thing (perhaps sold in by their agency), measurement is tasked to show that the decision to spend on these new things was indeed a good idea. So the organization drives the data that should be collected.
The “good” KPIs that come from this are whatever goes up. Ad impressions, site visits, content engagement, likes, shares, subscriptions. None of these have any direct profit-value to a business. Correlation might show that some are associated with the eventual generation of profit, but the data-driving organization never gets that far. They put the numbers that increased after the new stuff was tried into a dashboard and call it a day. (And if something really meaningful like sign-ups or sales isn’t measured to have increased — trust — it won’t make the dashboard.)
The Data-Centered Organization
The maturity level one step above the data-driving organization is the data-centered organization.
These are organizations that aren’t comfortable when they notice they are making decisions without data and analysis, but still haven’t fully developed their data and analysis chops.
They might still resort to expert-based decisions, but they don’t characterize them as “management’s (or the agency’s) conclusion for what we should do”. They frame this type of data-deficient decision-making as “management’s hypothesis for what will work best”. And they want to build up the data and analysis approaches that will allow them to test these hypotheses.
The intent to see expert-based perspectives as “hypotheses” and to build the capacity to make data-driven decisions are important steps in analytics maturity, but the most important distinction in maturity in this step is the willingness to invest in the generation of data without preconceptions of the conclusions it needs to prove.
Look, if everyone understands that data can deliver insights that create strategic advantage, why do some people think that this strategically valuable data will be easy to access off-the-shelf? Data that creates unique strategic advantage must be unique, meaning it will take some work to capture it.
Data-driving organizations don’t really value data, because they don’t actually need to prove the value of the decisions, since they’re allowed to make decisions without the support of data. It’s helpful if some off-the-shelf, easy to get metrics show some number that got bigger after the decisions. But no decisions are being blocked because there’s no data to support them.
Data-centered organizations see that data-driven organizations have strategic advantage from data because they have unique insights from non-commodity data; that they know and analyze things that other people don’t. They want to get there too. Both data-centered and data-driven organizations understand that something that generates value likely carries a cost to procure. So both the data-centered and the data-driven organization is willing to spend on generating data that will give strategically valuable insights.
Data-driven Organizations
The truly data-driven maturity level has been referenced throughout this post, so a quick recap as summary of this maturity level should suffice.
A truly data-driven organization puts the insights and predictive guidance from analysis ahead of any Sr. Manager’s or Executive’s expert opinion, or strategic intuition, or whatever decision heuristic these senior decision makers use that is based first and foremost on their prior experience and/or present seniority.
Strategically effective data-driven organizations hire and promote and utilize agencies in a way that gives decision-making authority to people who won’t just promote the insight from their experience — but who will actually test and analyze every possible decision with data until they find the one that holds up best in a predictive evaluation of what’s long-term best for the business.
Data-driven organizations have strategic advantage from data because they have unique insights from non-commodity data; that they know and analyze things that other people don’t. Data-driven organizations understand that something that generates value likely carries a cost to procure, so they’re willing to spend on generating and analyzing data that will give strategically valuable insights.
Most importantly, the operating culture of the business, the acceptable decision process, makes scrutiny of managerial hypotheses a norm. Managers are not defensive if their initial perspectives are questioned, they agree to turn to data and analysis to evaluate and even challenge that perspective. These cultures weed out people who are in management for their ego, for the rush that having authority gives them, and instead rewards the best insight wherever in the organization it comes from, which means also removing data silos through the organization and requiring some degree of analytic thinking in all roles, at all levels.
Which Are You?
The descriptions above have hopefully helped you understand which of these three types of organizations you are actually working within. If you haven’t yet, go take this quick survey to validaite your organization’s type.
