Data maturity used to be a distant hope – a “wouldn’t that be nice” – for many companies. Now, it’s become nothing short of a strategic imperative. Being able to effectively collect, manage, analyze and act on data can not only boost operational efficiency, it can drive revenue growth and create competitive advantage.
Companies that thoughtfully navigate the data maturity curve position themselves to make smarter decisions while better adapting to change. By aligning data capabilities with business goals and fostering a culture of data-driven innovation, organizations can transform raw information into a powerful asset that unlocks success.
A few statistics drive the point home:
- Companies with high data maturity achieve nearly 2.5 times better business outcomes, according to Heap.
- Organizations that excel at data maturity can experience 15% to 25% earnings growth in a shorter time frame, according to Forbes.
- One Gartner survey put the cost of poor data quality associated with low maturity at about $12.8 million per year, according to TCS.
In this blog post, we dig into how companies are increasing data maturity to drive success and consider some common challenges they often face along the way. We have some real-world insights from Collin Graves, CEO of North Labs, a fractional cloud data analytics firm. Graves recently joined the Alter Everything podcast to share how he helps leaders and individual contributors in companies enhance data maturity and develop trust around data.
Understanding data maturity
How well does your company leverage its data? Is it in the kind of shape where it can help you make smarter decisions, improve your processes and anticipate changes in market trends? Your answers likely reflect where you are on the data maturity curve.
A “data mature” organization has streamlined systems, reliable frameworks for governance and a culture that consistently prioritizes data-driven decision-making. If you feel like your organization is in a constant state of chaos around data, it’s likely because you are in the early stages of the maturity curve. If you have launched advanced analytics tools with predictive capabilities, you are well ahead of the curve and starting to see your data as a strategic asset.
Why does data maturity matter so much? For large companies with vast data sets, achieving data maturity can be a competitive differentiator or, conversely, an unwanted exposure. Here’s why:
- With mature data practices, you can analyze trends and uncover insights faster, helping you make smarter, more confident business decisions.
- Data-mature organizations automate workflows and optimize resources, saving time and reducing costs regardless of rising complexity.
- Companies with high data maturity are better positioned to innovate as well as predict and respond to market shifts
What role does trust play in data maturity efforts? Here’s where the rubber meets the road: trust is the bedrock of your entire data maturity journey. If the people in your organization don’t have confidence in the accuracy, integrity or completeness of your data, they are less likely to rely on it when making critical decisions. The hallmarks of a strong data maturity strategy (e.g., reliable, high-quality data, clear governance, etc.) are the very things that build that trust.
Graves stresses the need to quickly, efficiently develop trust of data within your organization. “Today, we have more data and more systems that create data,” he says. “We have more desire than ever before to leverage that data for decision-making or automation or operational excellence.
But the vast majority of organizations don’t know how to get started on that journey. And oftentimes what I see is that trust gets eroded. Maybe the data is unclean, it’s not assembled correctly, it doesn’t provide a ton of business value. To me, the underlying current of developing more sophisticated capabilities is: how do you continue to up the ante from a trust perspective so that people within your organization know that when they tap into this, it’s not going to lead me astray?”
Strategies for increasing data maturity
What strategies can organizations employ to increase data maturity? For starters, companies can take a quarterly approach that emphasizes having something tangible to deliver after every three-month period. “That’s a great balancing point,” Graves says, “between a couple weeks of effort, which doesn’t let you get very far, and a multi-year effort where things can become ambiguous and muddy.” This approach also helps minimize disruptions when requirements inevitably change.
Another effective strategy is to focus on specific outcomes rather than the broader benefits of data. Data skeptics still exist so it’s on leaders and analysts to educate and illustrate on a regular basis what data can do for the business and how it can bring measurable positive impact that increases over time.
Graves uses a manufacturing company as an example to illustrate the point. “Let’s say you use data to show that your scrap rate is currently 20% and the industry average is 14. What if we figure out where scrap is being produced and cut that difference in half? And what if it equates to $12 million a year in gross profit retention? Now you have a poignant story you can run with.”
What can leaders do to help? Advancing an organization’s data maturity is a team effort. It takes clear commitment from leaders and strong ongoing communication between leaders and analysts. Here are two ways leaders can pave the way to success.
- Start small, prioritize value: Graves suggests picking one key thing that needs improving. “You’ll probably think of 10 or 20 things,” he says. “Put them all on a whiteboard and noodle on them. Then rank which one is going to drive the most value for the business and be hyper-focused on solving that one thing.”
- Don’t cut corners: It’s important to use something like Alteryx to patiently build a solid foundation that will support the weight of future workloads. “I cannot tell you,” Graves says, “how many organizations over the years have been like, ‘Yeah, we know we need a solid foundation but we just need something quick and dirty for now.’” Don’t fall prey to that short-term thinking.
Get the data right and everything else flows
Investing in data maturity on a consistent, long-term basis takes work. It takes commitment. So what’s in the pot at the end of that rainbow? Graves argues the payoff for companies has been well documented. “You’re much more likely to be profitable,” he says. “You’re much more likely to beat your peers in terms of growth within your industry. Employee retention tends to be higher. And there are so many opportunities to leverage data for better operational excellence.”
This is about using the most powerful tools available to get a leg up, he says. “We’re no longer in an age where a spreadsheet and your spidey senses are the best possible approach to building a company. The only choice is to begin leveraging data because business is only becoming more complex.” By using data to remain nimble and be able to react in real time, companies can more effectively manage their supply chain, their marketing and much more.
Graves says it’s rare that a customer tells him their maturity efforts are going great. It’s hard work, he acknowledges. Graves urges companies to “start small, leverage the cloud’s ability to let you start small and let you be flexible, iterative and agile in how you do things. Then, once it begins working, build on top of it.” The payoff awaits.