Insufficient data management practices continue to be a major issue plaguing IT projects from implementation through achieving full functionality. Ben Thoren Director of Strategic Engagement at Optymyze explains that with 2020 just around the corner, now is the right time to fine-tune data fundamentals for the decade ahead.
The year 2020 always seemed like a space-aged futuristic one with visions of flying cars, robots and more. But now it’s right around the corner, and the reality is much different from the hype. In fact, when looking at it from a data perspective, 2020 appears to be a year where IT teams will go in the opposite direction and instead of jumping the gun on the hottest new technology, they’ll get back to basics and fundamentals when it comes to data management – at least that’s what should happen.
As we know, data management is how enterprises integrate data from all sources, cleanse it, and make it available for use in business-wide initiatives. But with advances in technology multiplying the types and sources of data exponentially, data management is more complex than ever before, and organizations struggle to extract its full promise by failing to create a data resource that is actionable. A recent study conducted by data firm SynscortOpens a new window found that 68% of respondents feel their data analytics efforts are hampered by data silos and that they can’t effectively deliver data to business users.
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In order for enterprises to extract truly transformative value from data, they will need fine tune their data fundamentals in 2020 to establish processes that more accurately collect, store, analyze and disseminate the data – and IT plays a critical role in that process.
Here are three key data management resolutions for IT teams in 2020.
1. Create a Single Source of Truth
The very first step in any data management process is to create a de facto “single source of truthâ€Â that puts enterprises in a better position to analyze key data and drive more effective business decisions. This can be achieved with the help of digital platforms that are able to automate the integration and cleansing of data from all enterprise sources – including CRM, sales performance management, HR and others. When enterprises connect all these data sources together, they will be more successful because:
- The data consolidation and cleansing process is automated, freeing up resources to focus on executing strategy rather than manual data entry.
- The data is clean and untangled, and paints a clear picture of past and present performance, allowing users to model predictive scenarios for all aspects of productivity.
- No-code approaches offered by many of today’s digital platforms means users can customize how they access and glean insights from that data without having to rely on IT, hire outside software developers or having to be data scientists.
There is a great deal of hype surrounding the benefits of predictive and prescriptive analytics, and indeed the development of these capabilities is a worthy goal. The truth, though, is likely that there are many areas of your business that are not yet fully equipped with quality descriptive and diagnostic analytics, much less equipped to contemplate the possibility of benefitting from predictive and prescriptive techniques.
For most organizations the reason why is the simple lack of a foundational, reliable data resource on which to build even basic analytics. In the race to pursue the latest and greatest trends, we shouldn’t miss the chance to bring value to the business at a much
more fundamental level by establishing a firm source of truth for further analysis.
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2. Become True Partners of the Business
It is increasingly important to dissolve the silos between IT and business to create a true partnership that drives tangible organizational impact. A 2016 study from McKinseyOpens a new window cited this relationship a business imperative, yet it’s been slow to come to fruition.
One fundamental way IT can become better partners of the business in 2020 is to provide democratic access to organizational data to those who need it. As part of its data strategy, IT departments should develop mechanisms that put data resources in the hands of those who can use and analyze it to solve key business challenges or develop new initiatives that move the needle. Prioritize investment in tools and technologies that facilitate these processes and allow for citizen data scientists to flourish without an over-reliance on IT teams or traditional data scientists – many of whom are already overburdened at work as transformative technologies (like AI) are rapidly adopted. As Gartner also notes, empowering citizen data scientists with access to data, and tools to analyze and act upon it, frees up highly skilled data scientists to tackle new challenges that are mission-critical to the organization.
Another aspect that will enhance IT’s partnership with the business centers around data management education. People tend to get really excited about the shiny new object, AI for example, and data management basics seem almost boring by comparison. However, the reality is tools like AI are only as powerful as the data organizations are putting into their systems in the first place, and without core data management processes your entire organization will be working off bad data. When the desired results don’t come, the business will be disappointed and reluctant to make good investments in the future. Set the expectations up front, and clearly quantify the value of this groundwork.
3. Prioritize a Governance Framework
Data governance provides a framework for the strategy and execution of data management processes, confirming that data is usable and consistent throughout the organization.
By strengthening the collaboration between IT and business, organizations are better equipped to define their governance framework – what should be a key imperative for 2020. Research showsOpens a new window that high-performing companies are twice as likely to have a strong data governance strategy and twice as likely to have a clear and well-understood data strategy overall.
As the volume and sources of data grow, so do complexities that can stifle even the most agile organizations. In 2020, IT teams need to focus their efforts on how data is collected, stored, analyzed, and how efficiently they make it usable to others in the organization. By prioritizing these resolutions, IT will create an efficient data management framework that maximizes the value of their data to drive strategy and business impact.