Research shows that roughly 2.5 million terabytes of data are created globally every single day.
When considering that data’s value is now comparable to the gold rush, this staggering statistic reveals the potential for profitable returns, but only for those businesses that can utilize the information they are amassing.
Following our advice on launching a data-driven business strategy, these pointers expand on how companies can unlock hidden value from their ever-growing databases.
Don’t just Hoard Data, Use it
In the last two years, most companies have increased their storage by up to 99 terabytes and expect to repeat that level of growth by 2020, according to InformationWeek’s 2018 State of Infrastructure Study. The thing is, most of that data is gathering dust, providing no value to anyone.
Many companies will fail to utilize their growing databases in a valuable way, due to a lack of a solid data-driven business strategy and an inability to analyze and act on the information they uncover.
By first identifying business goals that will bring value, companies can begin to set objectives that will direct their overall data strategy, revealing which of it is useful enough to be leveraged for profit. This approach lays the foundation for further exploration of the database.
For example, if the business goal is to improve customer loyalty by personalizing communications, then it is vital to target the information that relates to that goal, such as personal customer records, purchase history, and prior communications. This helps narrow down the search from the offset, aligning the most valuable data with the end goal.
With this approach, companies can avoid the risk of their databases becoming intimidating, unusable “swamps” and losing their value altogether.
Consolidate and Optimize for Consistency
Once setting a well-defined business goal, companies will often discover that their databases are disorganized, or unstructured, leading to a new set of challenges.
If a company is using a number of different storage locations, they are going to face issues with consistency—maybe the sales department is storing customer purchase history in one database and marketing has behavioral insights in another, for example. This is often a direct result of an organization operating across independent silos, so it is easy to anticipate in most cases. However, each database may also have a unique structure, or have messy, incomplete, or duplicate data, creating a time-consuming and expensive obstacle in the cleanup process.
This challenge of data wrangling, munging, or scrubbing—as it is sometimes called—requires a mix of automated and manual processes, along with the creation of standardization guidelines for how information will be collected across the entire organization.
There are powerful tools and knowledgeable professionals that can help with this, but maintaining a database that is clean and reliable requires time and commitment if companies want to generate real long-term value.
Turning Information into Actionable Insights
Even with well-defined business goals and clean databases, there is often confusion about how to act on the insights generated by data.
Data scientists may uncover interesting information from analyzing raw data, only to discover that it doesn’t help guide action towards the business goals. For instance, if the data reveals a surge in employee dissatisfaction, but the goal is to boost market visibility, then there is a misalignment with the analytics team and the company objectives.
While there are analytics and reporting tools to help with this, the main challenge lies in applying any resulting insights to the business in a practical, impactful way. This requires making analytics a core competency of the company, rather than relying on out-of-the-box software or transactional vendors.
With a combination of cloud platforms, reporting tools, and experts who can translate the insights into valuable business strategies, companies can start uncovering actionable insights that align with their overall objectives, forging the path towards true value.
Leadership Buy-in is Essential
Quite clearly, value generation from data is a complex task, a fact that often results in business leaders avoiding it altogether as they “let the experts handle it.” This is always a mistake.
Leadership must understand that data is a fundamental issue that impacts the entire business. Executives should regularly educate themselves on the insights being generated by their tools or experts, while also working to build a culture around data and preparing the whole company to take action on what is learned.
Value is driven by the performance of a company’s data, not just the fancy algorithms put in place by data scientists, or the organized structure of the database. In the end, that performance hinges on leaders’ ability to put data at the front and center of their business, where it belongs.