The need for enterprise-wide data strategies has never been stronger than during these days of always evolving computer platforms. Adding to this is the increasing need for all kinds of analytics to help drive a competitive edge and innovation over your competition.
One essential aspect of an enterprise data strategy is knowing that data can no longer be languishing in data silos. As many experts have stated, data is best when it is able to perform as an asset when shared and integrated across the enterprise as required. The data still has had an important role in the departmental level, but the enterprise can no longer afford to operate as if each of these departments function autonomously.
Many enterprises and businesses should make fast decisions in response to the unexpected and the constant changes in the market. The data and information underneath a business needs to be ready to go and fully integrated from the correct sources. To ensure the operational processes and decisions are based on trusted and holistic information, every analytics initiative should call upon data integration strategies that support the whole enterprise. All data integration processes should deliver business-usable and business-ready data.
Because data integration paves the way to many key objectives and is an essential part of data strategy, you have to remember that it:
- Leads to better decisions. Executive decision management relies on accurate dashboards and timely analytics to drive corporate business initiatives and corporate strategies. The right information or data is even more important for real time and self-serve analytics that get support from upper management and executive business users.
- Helps to grow revenue. Intelligence from existing customers and insights from their needs and behaviors should be shared across the enterprise to better understand and serve customers, help solve their problems, create new business opportunities, gain new customers and make an impact on retaining existing and loyal customers.
- Streamlines business operations. Access to timely and reliable information for departmental business and processes across the enterprise will ensure the visibility and consistency at every level of business operations.
- Ensures regulatory compliance. Consistency across the business with trusted and reliable data enables compliance, a clear audit trail, accuracy in reports and confidence in the quality.
10 Best Practices for Managing Enterprise Data
The quality of your enterprise data management is key in ensuring your business survives in this age of inter-connectivity. Having the right EDM solutions can go a long way in streamlining your business operations and increasing productivity that will directly result in better ROI. As we know, an effective enterprise data management solution doesn’t always come easy. You may spend many man hours and a great deal of capital in acquiring and setting up your data management solutions. Below are some best practices and suggestions to guide you in managing your enterprise data.
1. Know What Business Problem You’re Trying To Solve
With so much raw data to process, it is very easy for you to get lost. Therefore, having a mental road map with your overall objective will help keep your efforts on track.
2. Understand How The Project will Prepare Your Business
Ever-growing data and Big Data are legitimate concerns and they should be sorted out during the planning stages. It is essential to identify how your data management strategy will prepare you and your enterprise to cope with generic enterprise data and Big Data.
3. Formulate A Good IT Strategy
Any low-rate IT strategy can pull off any efficiently designed data management strategy. But, a good IT strategy will enhance and increase your chances of success.
4. Know The Business Values And Identify The Project Mission
A clear project objective and definitions of your business values will help in making a high return of investment. There should be a link between the initiatives and actionable insights.
5. Give Time For Evaluation And Thorough Planning
A well thought out plan will ensure all possible issues and solutions are sorted out before the project is rolled out. Any rushed projects will surely result in failure. You need the time and expertise to developing foundational data models.
6. Get The Best Platform
Choosing and getting the best platform is important. Putting in some expert research will make a lot of difference in the enterprise’s sustainability. The technology should be fool proof and should help the organization grow over the next few years without presenting or experiencing too many growth bottlenecks.
7. Pay Good Attention To Organizational Governance
A strong governance implementation that focuses and addresses issues like management change and knowledge transfer is important. After all, the culture in an organization is one of the most important aspects of having an enterprise and a solid plan to minimize any project risks will ensure success.
8. Stay Updated With Vendor-provided Patches
Your organization should plan and look forward to one major upgrade during the initial implementation because there will be a number of point releases, major upgrades and patches along the way. Make sure to build an upgrade competency plan for the team that will maintain the central platform once the initial project goes live.
9. Using A Holistic Approach
The people, processes, technology and information are the most important aspects within any organization or enterprise. Start with the people, the culture, the politics and make sure that you spend as much time on the business processes involving data governance.
10. Carefully Plan the Project Deployment
With the increasing complexity of EDM and MDM, the training of technical and business staff is very important. Any untrained or semi-trained personnel, DBAs, and outsourcing attempts can cause major issues and delay projects in the future.