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The World Has Changed. Is It Time to Revisit Your Data Management Strategy?

Authors Photo Precisely Editor | September 9, 2020

As the volume of data continues to increase exponentially, many companies are coming to the realization that there are hidden riches within their information systems. There is a rush to exploit that resource, and the companies with the most effective data management strategy to do that will have a significant advantage over their competitors.

Data is useless if it cannot be extracted, refined, and delivered to someone who can use it. An effective data management strategy lays out a clear vision for how an organization will capture data, work with it, store it, safeguard it, enrich it with both internal and external data, and create competitive advantage from it.

That strategy needs to evolve over time, as an organization grows and changes, and as the technology landscape continues to be transformed. The volume of data that is available to companies today is greater than ever. The advent of mobile devices, sophisticated CRM with digital marketing, the Internet of things (IoT), and cloud computing have all combined to generate a volume of information never seen before. As 5G technology begins to take hold, that trend will accelerate even further.

A company that had a great data management strategy five years ago might find that it needs to re-examine its vision and make some changes. Here are some of the indicators that your data strategy might need an overhaul.

1. You have added or significantly upgraded new systems

If your company has rolled out a new ERP system or upgraded your existing one sometime in the past few years, then you have probably been grappling with the migration of data to the new system, management of your historical data, and the desire to maintain a consistent vision of your organization’s data across the time span in which you made that change.

To put it another way, you may need to figure out how to compare apples (data from yesterday’s ERP system) to oranges (data from your new system). If your focus has been primarily on rolling out a new system and migrating data, then it is likely time to shift your attention to the big picture.

This scenario doesn’t necessarily just apply to ERP, though. Significant changes to CRM, e-commerce, digital marketing platforms, or other information systems should also prompt a review of your data management strategy. Do all the pieces fit together? Are you missing anything? Have you normalized data from legacy systems to conform to a data model that serves your current needs?

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2. You have added new divisions or product lines

A similar scenario may arise out of other major business changes. If the organization adds significantly new (and different) components such as a new division or region, or a new product line or category of service, then it may be time for a review of the data management strategy.

Those changes may be driven by regional or regulatory requirements, additional software systems, or different data models that conform to processes and management practices for a new product, for example.

3. You have implemented digital transformation technologies in your organization

If your company or organization has embarked on a project that makes use of relatively new technologies such as IoT devices, GPS, drones, blockchain, or similar “digital transformation” innovations, then it is likely that you will be generating larger volumes of data than ever before.

For instance, a company that is tracking shipments with IoT sensors that report location, temperature, humidity, and other information on in-transit products will suddenly find that the volume of available data has increased dramatically. How does that data fit into the bigger picture? Can it be used to inform better business decisions? If so, how?

4. The regulatory environment has changed

As the volume of data grows and data sovereignty and privacy issues continue to be the subject of public scrutiny, governments are imposing regulatory changes that can dramatically affect data management practices. The European Union’s General Data Protection Regulation (GDPR) has had far-reaching implications for the way that companies store, protect, and retain data.

Although GDPR is the best-known and most far-reaching example of such regulation, numerous governments around the world have enacted or are considering similar legislation. As privacy and security concerns continue to mount, this trend is unlikely to go away anytime soon.

Data sovereignty, likewise, has been a subject of considerable attention, and a number of governments have issued regulations mandating that certain data be hosted domestically. Companies must assess whether their current data management strategy supports rapidly changing regulations and, if not, what must be done to provide that support.

5. You haven’t been getting clear, reliable insights from your data

Ultimately, the measure of your data management strategy is the value your organization gets out of all that information. If you have clearly defined what’s important and what’s not, if you are able to derive meaningful insights from your data, and if stakeholders throughout the organization have a common vision of how data can drive strategic advantage for your company, then you have a solid data management strategy… at least for now.

As the first four points in this post suggest, however, every data management strategy needs to evolve as the organization and its technology landscape change over the course of time. If stakeholders throughout your organization have ceased to see data as a strategic asset, or if they feel that the organization is no longer getting reliable, actionable insights, it is a good indicator that it’s time to review your data management strategy.

A strong data management plan should also look to data enrichment using outside sources, such as geospatial information, demographic and consumer data, and other sources that add value and insight for your business.

Like any strategic plan, a data management strategy must strike a balance between being a long-term, big picture vision and being a living, evolving plan. In other words, it needs to be flexible and changeable, but not too much so. A strong vision for managing data as a strategic asset can be a key driver of competitive advantage for organizations that treat it as a priority.

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