A Collaborative Approach to Building a Strong Data Ecosystem

Lyndsay Wise
May 13, 2020

Organizations manage a lot of moving parts – data comes from many different places and sits on disparate platforms across on-premise, hybrid, and cloud solutions. In many cases, integrating data and getting systems to speak to one another presents a whole set of challenges outside of traditional data management.

The marketplace is finally addressing this need and creating open systems so that competitive offerings can work together in an integrated way. This is a game-changer for how we think about and approach data. The new digital landscape impacts how we create end-to-end solutions to automate and deliver insights in context for actionable intelligence. Organizations can now look at their data assets and platforms as pieces of a puzzle and not just disparate systems that require integration. Building strong data ecosystems is an important part of this process.

Open and Data-Driven

Stakeholders no longer have to spend their time selling the value of strong data management internally to organizations. Most companies want to become data-driven and design solutions that are focused on digital transformation – even if quantifiable benefits are still being discovered. This is where data ecosystems come in. The adage "garbage in, garbage out" applies to data ecosystems, and unless people have access to all the data they need in a consolidated and validated form, they won’t be able to realize true business value.

This requires two sets of considerations – 1) The technical requirements to ensure a complete and valuable data ecosystem, and 2)  The outputs needed to ensure the delivery of valuable information and actionable insights. Each of these is complex, but here are some key considerations to get your organization started aligning data and platform needs across the organization. These are by no means comprehensive, but should provide you a good starting point, from an IT and business perspective.
 

Data Ecosystem chart


Three Considerations for IT Stakeholders

  1. The where, what, and why of platforms: Everyone is talking about how and where data is stored within organizations, as many of the platforms and solutions are being installed in the cloud. The question organizations sometimes overlook is the why: Why are we selecting this specific platform? Why do we need to support a strong data ecosystem and how do we achieve this? In order to get to the why, several questions need to be asked first. For instance, where does the current data reside? Do data access gaps exist? And what is missing in general? Basically, organizations need to be continually asking questions about what they are doing, why they are doing it, and the level of success they wish to achieve.
  2. Integration is more than putting the pieces together: Organizations need strong data governance, security, privacy, and collaboration. It isn’t simply how data is integrated and managed, but also how the data ecosystem enables end users to interact with that data and make sense of it. Much of this actually falls outside the realm of data activities and requires collaboration across the organization to develop a process-driven framework to manage these components.
  3. The realities of openness: As more vendors and solution providers become open, this does not mean that integration challenges will cease to exist. The reality is that you are not going to remove all legacy systems at once. And not all of your providers will be open. As such, integration efforts still take time and require agility to be successful over time. The development of an end-to-end data ecosystem will become easier in the future as more solution providers deliver APIs and an open framework approach.

Three Considerations for Business Decision Makers

  1. Understand the business impact of data: Too many organizations work in departmental siloes and do not map the concepts surrounding data efforts with business outcomes. Any data ecosystem project should start with the end goal in mind. Understanding how information can and should be leveraged provides development and IT management teams with the information needed to develop a back-end offering with front-end use in mind.
  2. Data cannot exist in a vacuum: Understanding customers, competitors, suppliers, partners, ecosystems, etc. means having visibility into data. The more visibility, the better. Being able to provide context will lead to more quantifiable business benefits. Data across the ecosystem needs to be understood from an overall perspective: how to manage it, how it will be used, and how to gain value from it. This requires working cross-functionally to ensure that data assets and how they are managed across the organization link to business value and desired business outcomes.
  3. Empower people by giving them autonomy: The most value data can provide is autonomy. In addition to better efficiencies, lowering costs, increasing profits, and so forth, the reality is that visibility into data gives people autonomy to make better decisions and to have access to all of the information needed to empower them to do their jobs and contribute more to the organization. The culture of better, more informed decisions making across the board lifts overall business performance and embeds innovation in every interaction.

Getting It Right Through Collaboration

All of these considerations just touch the surface, as each is part of a larger initiative in and of itself. Developing a data ecosystem requires an in-depth evaluation of many different data and strategic considerations, making it complex. Both business and IT stakeholders must come together to collaborate and leverage data as the "great aligner" to drive company-wide objectives and key results. Lastly, we must recognize that developing a strong data ecosystem is iterative and agile based on continual change and growth within any data environment. 

 

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