In the digital age, data ceased to be just a byproduct of business activities to be discarded after it served its purpose. Today, data is the new gold, so valuable it requires not just management, but a serious strategy for businesses to harness its benefits.
What’s the difference between data management and strategy? Think of data as your money that as you’re running a business, you wouldn’t just manage but actually grow. And growing money is an activity that needs a strategy.
As the Internet, social media, mobile, and the digital revolution continuously pump data - containing valuable business information - into organizations, it’s almost a crime not to have a strategy to effectively mine it.
What does an effective data strategy entail?
It starts with what your business wants out of data. Generally, a data strategy is created to support the organization's overall business strategy, which aims to increase profit and market share, decrease cost, differentiate products through innovation, and deliver an excellent customer experience.
These can only be achieved through quality information distributed to relevant personnel and applied to the right systems and processes. That’s why data quality management (DQM) is the most important business intelligence (BI) trend for 2019.
So, what are the basics of an effective data strategy?
- Identified and defined data. Much like how books are cataloged and organized in libraries, data must also be named, formatted, and assigned values.
- Storage. Since data is an enterprise asset, the organization’s storage capability must accommodate not just data housing, but also convenient data transferring and sharing between systems.
- Rules and access guidelines. To ensure consistent data management, enterprise-wide data governance rules and policies must be established.
- Data processing system. Most if not all data comes into the system raw. Meaning, since they’re from different sources, it’s anticipated that they’ll be in different formats and levels of quality, and must therefore be cleaned and enriched before being sent out.
Quality information or valuable insight, such as granular customer and competitor details should come out of these activities. And once acquired, these insights should be correctly and swiftly acted upon, for example, if certain products are doing well on certain channels and at certain times - then not only should heavier advertisement and promotion be sent that way, but a more focused data mining activity to find out why it’s working and how it can be improved to not only drive sales but inspire brand loyalty.
How is MDM central to a solid enterprise data strategy?
No matter how good the drawn-up strategy is, it won’t work without proper execution. And to execute well, you need a modern master data management (MDM) solution.
Gartner defines MDM as a "technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets."
It ultimately gives you a single, trusted version of the truth or golden record, which enables you to have a complete picture and a deep understanding of the relationships between the data entities relevant to your business, such as your consumers, products, suppliers, stores, etc.
With MDM, you can:
- Ensure data quality.
- Assign roles and responsibilities
- Establish processes according to your business requirements
- Acquire, process, and model data from multiple coexisting domains
- Share information within your business
- Integrate assets/content from different sources
Your enterprise data strategy is your roadmap to fulfilling a long-term goal. An MDM is essential for your journey as it allows you to regularly review and measure your activities, so you can continuously grow and evolve into an organization or brand that constantly transforms to the needs of your consumers.