Author:Michael Hatfield
November 29, 2021
Data-driven Decisions: Focus on (surprise) the Decision Makers
Trying to build a data-driven culture? Focus on the right persona, not the builder, and you may have a better chance.
4 min read
Technology cannot create your culture, but it can make user adoption easier.
Bar chart. Pie donut chart. Scatter plot. Box plot (I still call it “box and whiskers” from 2nd grade). Network node. Radar. There are about 300 others, and I have built most in the last decade (15 years) to translate data findings to organizational decision makers. I stand by this: as a medium to call out anomalies, trends, and facilitate findings these charts are good, some of the best. My boss will want to switch to the Minority Report gloves when they’re ready, but for now dashboards work pretty well for displaying and (if done well) interrogating data.
But here’s my thing: there are loads of (and growing) tools to do the building, but they still aren’t helping the decision maker do what comes next: make decisions.
They help the analyst build a bit faster, a bit easier, or with a cool new look/feel. Some integrate AI/ML, while others speed up data prep for the analyst… all great. There’s plenty of data, analysis, analytics and content. But when the dashboard or suite of analytics get to the decision maker what happens? They still stare at it, wonder about the underlying data, interact with it and have questions…and that’s good! In most of my experiences, they take these questions into a slow cycle of meetings, which increases the time to value and actionable results. Or, they take the beloved screenshot and start a static conversation disconnected from the analytics.
I care about this because it can lead to mediocre ROI on enterprise analytics and a terrible user experience that is sorely forgotten. There’s also time wasted screenshotting, exporting data for ad hoc analysis, and preparing presentations that are often incredibly wrong or misleading as a result of “laundered” derivative content. Here’s the outcome:
Best case:
Leaders, decisions and teams use data when making decisions, but it’s a painful process that has become accepted. The already-mediocre ROI promised by BI is further diminished if you quantify the wasted time I outlined. That wasted time multiplies across any organization as people chuck info into single-use PPT decks, and retrace their steps through emails and screenshots later in the process.
Base case:
the analytics are so difficult to get to or keep track of, the leaders direct an analyst to snag a few screenshots or a static one-page that tells “their story”. With little understanding of the data or the whole story, this oversimplified view is dragged into meetings of great consequence, vouched for as complete truth.
The WORST (case):
decision makers give up due to difficulty, time or doubt and make big decisions with their gut (to be clear, leading with imperfect information is crucial at specific times), that could have been made with informative decision points and analysis.
Without more meetings or a lot of re-work, I contend that it’s not easy for decision-makers to put analytics at the center of their decision-making process. How can you develop and live the life of a data-driven decision culture if it isn’t easy to do within the business? I agree, technology cannot create a data-driven culture, but I am betting that technology that makes the process of decision-making easier, with decision makers as the focus, will give an organization a better chance to succeed at becoming “data-lead”.
If this resonates for you, watch this space as we fixate on this problem, and all interrelated topics as we continue our own product journey. We will see if it is possible to increase analytics ROI and decrease time to value by placing more focus on the combination of analytics, the user persona, and the current friction that exists.
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