Do you want to use your company data potential profitably? Have you already started projects, or are you in preparation? Or, as IT managers, can they provide the data or build an Analytic platform?
No matter from which perspective you deal with data, a basic requirement is always a clear strategy. For a start, the later course is a guideline and yardstick for the success of your projects.
In our view, strategy development includes the following eight aspects of success:
1. Ensure A Good Control Structure
In contrast to many other IT projects, the use of data is often a cross-sectional task with many tasks to be solved and a large number of participants. For example, data from different systems must be collected, described, and cataloged to be evaluated by other areas. Technologically, the data from the individual systems must be collected, processed, and made available on analysis platforms. All of this must take place on a technically and legally secure framework. This automatically results in a large number of dependencies to be managed, which are crucial for the successful progress of your projects.
Determine who is responsible for developing and managing your data strategy. Find the right organizational framework for you to manage your projects holistically. Please provide a good mix of professional expertise and IT know-how.
2. Determine The Data Potential You Are Concerned With
In the beginning, it is about recognizing the potential benefits you associate with analyzing your data. These potentials are only sometimes tangible or measurable at the beginning. Nevertheless, starting with reasonable initial goals is helpful to gradually evaluate them in the further course. Instruments for this are use cases or scenario techniques. You will get an overview of the potential benefits and objectives of using your data. On this basis, deciding what you want to focus on is advisable. The clearer and more concrete your vision, the faster you will achieve your goals.
3. Determine Your Procedural Strategy
The implementation strategy is closely linked to the data goals. In it, you determine the steps by which you want to achieve your goals. There are different models of thought here. Due to the i.d., an agile and learning approach is recommended for the high complexity of the projects. It helps to achieve quick and visible results. It is about more than one IT topic – the optimal collaboration of different actors in different areas and levels.
4. Develop A Comprehensive Data Management Plan
Keep all elements of data management in one central document for all stakeholders firm:
- Data categories
- Access rights
- Storage locations
- Permitted file formats
- Data protection regulations
- Preferred external companies
This data management plan is not a static document but a data record that is changed dynamically. Determine a person who is responsible for ensuring that the DMP is tracked continuously and that everyone is involved in the changes.
5. Use Tools To Control
To ensure that compliance requirements are met, you should use data warehouse tools. These help you record, track, and monitor personal data storage locations and connection chains. Make sure that the person responsible for compliance monitoring knows these tools.
6. Create A Data Collection Level
The data acquisition level forms a layer above the data queries. It is comparable to the catalog of a library. Here, the analysts are looking for suitable data records that they can use for evaluations. It is important that they can be used for evaluations. This search platform must include all memories, no matter where they are, and the storage model.
Invest enough time in defining and implementing suitable search criteria. Talk to the users. Find out what they are looking for, which analysis tools the data requires, and which metadata must be available.
7. Start Small
Experience shows that many data projects need to be revised because the complexity is getting out of hand. Your investment can quickly develop into a bottomless pit. It is common for such projects to run for several years. Too many topics have to be solved at once. That overwhelms your organization.
The art is to think in small speedboats. How about leading one of your data-driven projects to the goal within a few months, thinking in clear components, and learning for subsequent steps? This procedure is scalable. In the next step, you can start with several speedboats if necessary.
8. Putting It All Together
You don’t have to be a data-whiz kid or certified analyst to leverage data successfully for better business decision-making. You do have to develop a plan, try out new strategies, and commit to prioritizing data as you move forward. If you’re willing to do so, good things will happen.
Would you like to use data more effectively for your company? The ExistBI experts analyze your requirements, support you in creating a data strategy, and implement your data storage solution. We offer various cloud and on-premises models. Contact us now for an initial non-binding consultation.
