Shelfware Hidden in Plain Sight: Your Data
Discover why empowering employees with data access and analytics tools is crucial.
Trevor Schulze, SVP and chief information officer of Alteryx, explains how to eliminate data shelfware by creating a flexible data architecture, providing self-service tools, and fostering data literacy within your organization.
All IT professionals should be familiar with the meaning and existence of shelfware and should be clear on how they’re going to eliminate it. After all, shelfware—software that never gets used—is a waste and could potentially cost your organization millions of dollars.
However, shelfware extends beyond software and applications. Your organization could be losing much more than that by overlooking a treasure trove hidden in plain sight: your unused data. Think about the untapped potential: as much as 80% of industrial data never gets used.
Between skills gaps, overly complex manual processes, and incompatible technologies, there are many reasons why data goes unused. It also doesn’t help that 65% of organizations believe employees who make decisions for the business should not have direct access to data.
As companies continue to grow, so will their data footprint. But instead of overspending on disparate tools to manage and analyze this mountain of data, organizations should focus on responsibly empowering more employees to transform this data into insights at scale. This strategy requires designing a data architecture that the business can easily use, providing self-service analytics tools for non-technical domain experts, and prioritizing data literacy across the organization.
Here are some best practices to make your data stack usable so that your data itself is usable.
Build a Flexible Data Stack That Reaches the Data Wherever It Lives
One reason data might go unused? It’s trapped in disparate systems, like legacy on-prem databases that go unused or a data lake that has become a disorganized data swamp. Or the difficulties and costs of import and export across multiple data sources and hosts cause analysis to grind to a halt, leaving your data idle.
To start, choose solutions compatible with all ecosystems so teams can more easily access and analyze their data. Many versions of the modern data stack lean on cloud capabilities, but the reality is that most organizations are managing more complex data pipelines–on-premises, hybrid, across multiple clouds, and so forth. To successfully navigate this complexity, you need capabilities such as pushdown execution, which reduces friction by letting business users work with data directly where it lives.
Deploy the Right Toolsets to Help Users Turn Data Into Insights
Next, consider how employees across the business are equipped to solve your most complex problems with data.
The first step to tool adoption is to give users a voice in the process. In this case, loop in your business stakeholders before investing in technology. You want to understand and assess their use cases, pain points, and technical knowledge so you can deliver a solution that will help them derive value from data. Otherwise, expect your list of shelfware to keep growing.
Seek out an analytics platform that enables the business to access data, transform and analyze—even build machine learning models—and deliver automated reports from a single interface where professionals of all technical acumen can collaborate. Simplicity is often underestimated in this scenario. Adding more tools to solve niche problems won’t make your data more usable. Instead, tool proliferation leads to more data silos, new complexities, and even more shelfware.
This situation highlights another issue many organizations face: a data skills gap. Giving employees access to data and the tools to analyze it won’t help if they don’t have a solid understanding of how to work with data, ask questions about data, and solve problems with data. Companies and their IT leaders must support building data literacy and upskilling employees so they can make data-driven decisions.
To take the greatest advantage of your data in today’s intelligence era, encourage collaboration between non-technical employees and your data-savvy experts on a single platform to increase the quality and accuracy of your insights. As a bonus, non-technical employees will learn new skills faster and get even more comfortable working with data. After all, analytics is a team sport, and the more you can pair domain experts with technical experts, the faster you’ll arrive at your destination.
See More: How Immersive Data Experiences Enable Decision-making
Set up Robust Governance Frameworks
Our work here is done, right? Several things cause heartburn, and giving everyone access to all data is at the top of that list. But if you don’t make data accessible, no one can use it. And then you’re stuck with data that’s shelfware.
Once you have the tools and infrastructure to enable employees to use data in their day-to-day work, you need robust governance policies to prescribe the methods people can use to access and analyze data. A framework provides a structured approach for defining roles and responsibilities, developing policies and procedures, and implementing tools and controls.
Further, we asked 3,100 IT and data leaders and professionals to rank the governance practices required to ensure their organizations’ data is high quality and delivers value. They noted the following: data is kept secure (40%), data is regularly validated to ensure accuracy (35%), and data is kept up to date (34%).
Governance isn’t a roadblock. By taking a proactive approach, governance helps ensure data is checked for accuracy and completeness and delivered to the right place, which leads to improved decision-making, reduced risks, and improved organizational performance.
Implemented effectively, governance makes data more usable and prevents it from accumulating dust on the shelf.
Start Now and Iterate Over Time
Your business is constantly evolving, so be prepared to continuously align and collaborate with your stakeholders in designing your data stack to maximize the value of all your data. Don’t wait to get started: as we begin the new year, now is the perfect time to ramp up your journey to eliminating data shelfware. Make wise investments that help your organization assign meaning and value to all your data and continue to empower everyone to transform this data into intelligent decisions through upskilling and self-service tools. Tapping into your treasure trove of unused data will help you drive innovation, solve complex problems at unprecedented speeds, and help your business enjoy its most successful year yet.
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