4 Principles to Inspire a Truly Data-Driven Culture

To start, stop neglecting your data.

Written by Grant Shirk
Published on Jul. 31, 2020
4 Principles to Inspire a Truly Data-Driven Culture
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Ask any business leader or startup CEO if they want their business to be data-driven and the answer will be a resounding yes. But even for these forward-looking companies, a data-driven culture remains frustratingly out of reach.

Businesses today operate in what feels like a golden age of data, collecting terabytes of information on customers, products, and performance that could be used to inform every daily decision. And yet, even the most data-savvy companies are using only a small portion of that valuable context.

As 451 Research’s research vice president Matt Aslett explained in a recent webinar, the average company uses less than half of its data available for analytics, but that utilization will likely double in two years.

With such treasure troves of data being neglected, companies are left to make critical decisions based on gut instinct or a partial view of their data. Certainly, making smarter, informed decisions faster won’t come from collecting more data. Instead, companies can accelerate their journey by creating a culture that naturally turns to data, not assumptions, to make decisions.

There are four principles a company can adopt to stop squandering the value locked away in data and start building a culture that thrives on data-driven decisions.


Lead With the Facts and Others Will Follow

It’s easy to talk about informing every decision with data, but it’s a lot harder to make this an instinctive approach to every decision.

Start by leading by example. As recently explained in the Harvard Business Review: “[S]et an expectation that decisions must be anchored in data — that this is normal, not novel or exceptional.” Building a data-driven culture requires leaders to demonstrate that all decisions — from product design to marketing campaigns to hiring and performance — are based on data. The goal is to have that ethos permeate throughout the organization.

In practice, this takes shape in ways both small and large. For example, managers should reinforce this expectation by consistently asking questions in meetings about the analysis behind recommendations. In internal communications, companies should showcase and promote teams who visibly use analytics to make decisions. And when given statistically rigorous analysis, leadership should be prepared to be bold and decisive — especially when the data contradicts their original strategy or hypothesis. Avoid the temptation to revert back to gut feelings.

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Adopt Tools That Inspire the Daily Use of Data

For many companies, its not a lack of desire that keeps them from basing decisions on data, its not having the right tools to access, analyze and act on all of the rich data they capture in real time.

Fortunately, the rise of cloud-native data warehouses like Snowflake, Redshift, and BigQuery makes it easier than ever for companies to store massive amounts of data. Unfortunately, most modern business intelligence (BI) tools were built for an earlier generation of on-premise data stores and just aren’t capable of putting that rich data to work.

These limitations have forced data teams to waste hours manually massaging the data to aggregate, simplify, and streamline complex data sets into narrow, simpler views. But that’s like downsampling an audio file — you lose too much of the richness in the process. As a result, decisions suffer.

Fortunately, there’s a new generation of cloud-native analytics tools purpose-built to wrangle these massive data sets and augment your company’s ability to find the facts buried in the data. These new platforms make it easier for teams to use data in a daily, operational cadence by leading with what matters most — the KPIs that define performance — and automating the process of exploring the data. This approach gives more people in the organization self-service access to answers without requiring advanced data skills.


Diagnose the Why, Not Just the ‘What

To surface actionable answers about your business from your data, and provide your business with answers in real time, you need to make sure you’re answering the right questions. Most organizations are equipped with dozens of reports, dashboards, and embedded visualizations that describe the “what” in their metrics — what metrics are changing, when the change occurred, and how big that change is.

So what’s the problem? The issue is that “what” doesn’t inform what’s next, and for every “what” we can answer, there are countless questions about “why” the change happened in the first place. These are the most valuable questions a leader can ask.

The trouble is that answering the pointed “why” question involves checking thousands, if not millions, of possible hypotheses, kicking off hours of data collection, exploration, and hypothesis testing. And when time is short and the team needs answers now, there’s no way to check every possibility.

Fortunately, a new wave of proactive analytics platforms are emerging to accelerate the two most common drivers of why: root-cause analysis and anomaly detection. These platforms accelerate diagnosis and focus teams’ limited attention on the highest-impact drivers of change with timely, relevant findings and recommendations for new questions to ask of data. As you seek the “why” in your data, picking a platform that works within your existing decision-making process is key to success.

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Embed Analysts in the Business to Accelerate Understanding

The last pieces of this puzzle are the pace and process. Building a culture that thrives on facts, consumes data daily, and asks the right questions, cannot succeed if these processes slow down the pace of business. The speed at which you can diagnose changes in the data and recommend clear actions will be the difference between success and failure.

But the only thing that grows faster than the data you’re collecting is the sheer number of questions decision-makers ask of it. As the gap between what you need to know and what the team can answer grows, even the most stalwart organizations will grind to a halt.

There are two immediate ways to close this gap and accelerate the pace of decision-making. First, ensure the analysts in your organization are not only embedded in each business unit but are actively participating in the rhythm of the team. If analysts are not directly involved in the daily and weekly cadences of decision-making, the process will inevitably falter. Every business unit needs a dedicated analyst team to thrive.

Second, invest in tools that further augment an analyst’s innate skills of speed, interpretation, and storytelling. By doing so, they’ll be able to reach more of the business, examine more data on a daily basis, and inform more operational decisions. With better, faster, more proactive diagnostic platforms, these expert analysts can quickly answer more questions in a shorter period of time and catch up with the tides of data flowing into the business.

By involving analysts in the decision-making process, not just when you have a question, you give analysts the context they need to explore the data faster. Embedding analysts in the business will train every individual stakeholder to think like an analyst. And when stakeholders across the organization begin thinking this way, it will rapidly reinforce the cultural norms of asking more effective questions and confidently using data to make decisions.

Building a truly data-driven culture will unlock the full potential of your company. Trusted, comprehensive answers from your data provide employees with the confidence they need to tackle new challenges, and allows the company to continue moving forward even with unprecedented changes. But a data-driven culture doesn’t happen by accident, it’s an intentional, habitual process that you should start fostering now.

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