These days businesses are able to access and use more data than ever and moving forward this will only increase significantly. Using Data effectively to measure, learn and improve is crucial for everyday business decisions, and effective Data management processes and solutions ensure the availability of the accurate and reliable data required to enable informed decision making.
Data management plays a vital role in making business decisions easier and faster by adding structure, automation and control to the collation and availability of a business’s data. Ensuring that the information is always accurate, up-to-date and readily available in the format and context needed.
Effective Data management can take many forms, some of which may sound scary or unnecessary. However, if you are creating or using data or manually created reporting for operational or strategic decisions, you are potentially undertaking some of the following but without any structure, controls or security.
Here are 6 Reasons why Data Management is important:
With so many ways of creating data in a business, having robust data management processes creates a solid foundation. From there you can ensure that your data is stored in a way that provides accurate data for reporting, analysing or regulatory requirements. It also allows you to create plans and procedures that allow for the inevitable increase in data volumes.
Whether you use data for reporting and analysing or have to store for compliance or regulatory reasons, the accuracy of the data is critical. It creates confidence when used to make operational decisions, and long-term engagement for strategic measurements. If you hold any type of customer information, making sure you have full knowledge of what data you hold and that it is 100% accurate at all times is a requirement for GDPR and other industry regulations.
Keeping your data secure at all times is not only subject to regulations, but critical for the ethics and reputation of a business. Data management will put in place a suitable environment, robust processes and rules that ensure your data is always secure and accessible by people who are authorised.
For example, a team member accesses data about customer orders and downloads to excel on a laptop, then takes the laptop from the office. How secure is that data?
Aligned with Accuracy, data management creates consistency across a business and all its departments. The content of reporting and analytics has to mean the same thing for the whole business, otherwise you have a disjointed view of how the business is performing, what the challenges are, potentially missing them and upcoming opportunities as well.
For example, it’s obvious to the eye, however if used in a calculation of sales/profit or costs there is the potential for a mismatch without manual intervention.
Department A reports: Client Abc123-London Product.98765
Department B reports: Client Abc123a – London-UK Product.98765
If you currently have or are planning to use data analytics within your business, data management creates a robust environment ensuring the accuracy and consistency of the data when making business decisions. It allows you to create reports and dashboards that can be used daily, weekly or monthly by developing processes to keep your data up to date. Meaning a huge amount of time is saved by avoiding creating the data and outputs manually over and over again.
Data management allows a business to measure and report on the processes and activities that ultimately determine a business’ Strategic performance. As a business you have overall Strategic goals; typically, these can be a mix of financial and non-financial metrics. Aligning your Data strategy to your Business Strategy means you can consistently review how day to day operations are performing, and how that impacts on the longer-term Strategic outcome.
For example, think about taking a high-level Strategic target, and defining what operational activities determine whether this is achieved. Then defining a suitable KPI/metric to measure if this is achieved. Then repeat the process for that metric. This is typical of a Balanced Scorecard approach.