A clear majority of corporate executives think their teams aren’t using data and data analytics to drive business decisions. Even more are uncomfortable accessing or using data.
That’s according to a 2019 Deloitte survey of business leaders. The survey found that 63% of business executives believe their teams are not “insight-driven,” meaning they aren’t using data to drive strategic and tactical decisions. Two in three surveyed executives (67%) reported that they were not confident in their abilities to use the data generated by their own teams. The discomfited share decreased but was still significant (37%) in companies with robust data cultures.
These results are sobering in part because they’re preventable. From sales and marketing to logistics and business processes, the inherent value of a comprehensive data strategy grows clearer by the day. Behind-the-curve enterprises simply may lose significant market share in a world where data rules all.
There’s no time to waste. Wherever your organization is on its data journey, use these four strategies to make the most of the information it collects.
1. Model Your Data Infrastructure After a Well-Oiled Machine
Modern data systems are built on multiple machine-based technologies. Typically, these systems don’t provide the granularity or insight that is critical for data teams to support, manage, and move data across the enterprise. When unexpected outages occur, it’s all hands on deck to get the systems back up and running.
Reduce the risk of unexpected data emergencies by keeping close watch on your data at the infrastructure or data compute layer. You can’t scale or optimize your data initiatives if you’re fighting frequent outages and performance degradation issues.
Shore up this process with a data observability solution that, per business intelligence provider Acceldata, can “predict and automatically fix issues before they impact performance or create unplanned outages, cost overruns, or bad output based on low-quality data.”
2. Identify and Segment As Much of Your Data As Possible
If you can measure it, you can manage it. That might as well be the golden rule of data science. On a more practical level, it’s a crucial organizing principle for data-driven organizations.
The data consumers using and interpreting your data need to know exactly where each bit or type of data comes from, what processes it illuminates or informs, and what it means in the broader context of your business strategy. A common issue for data scientists is that they spend almost half of their time finding data, making sure that the data is current, and making sure the data is accurate.
3. Develop Your Data Linkages
Knowing where your data comes from and what it means is a strong start. But organizations that have truly mastered their data go one step further and assign direct linkages between collected or processed data and business process outputs.
For example, virtually every business that ships or stocks physical products relies on real-time location tracking to inform strategic and tactical decisions around inventory management and fulfillment processes. The value of this type of data usage is so clear that it’s done without a second thought.
You know your data better than anyone, so you and your analytics teams are best-placed to develop these linkages, including those that are similarly self-evident in your own business context.
4. Make Your Data Legible, Accessible, and Secure
Your data is useless, or at least less useful, if it’s not easily understood (legible), accessible to those who need it, and protected from those who don’t need it. Your company should establish data governance to define who can take what actions with your data. Other steps to keep a hold of your data include:
- Use rich subjective descriptions and metadata to convey the contents and purpose of data sets
- Utilize secure data management platforms and workspaces to ensure your organization’s data is accessible when and where needed
- Develop a hierarchy for data importance and sensitivity, linking access permissions accordingly
- Utilize multiple layers of data security, all linked by the principle of least permissions, to curtail insider threats and keep your data invisible to outsiders
- Anonymize user data wherever possible to ensure regulatory compliance and reduce the risk that your data-rich strategy backfires over privacy concerns
Make Your Data Work for You
Your company’s data is its most valuable asset. You need to make sure it’s working for you at all times, as efficiently as it can.
Like any valuable asset, data does best when it’s leveraged effectively. Each of these strategies, from maximizing your data infrastructure and visibility to mitigating risk with best practice data governance principles, works to that end. Because sound data-driven decision-making isn’t only about making data work for its owner in the here and now.
It’s about ensuring data works efficiently and sustainably for months, years, and business cycles to come.
