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The internet has taken the bulk of our lives online. Business is conducted through websites, social media dominates our personal lives, and ecommerce has overtaken bricks and mortar shops. Even in the real world, technology now impacts nearly every aspect of our existence. Watches monitor our heart rates, heaters can be controlled remotely, and we unlock our phones with biometric tech.

These digital activities all leave a trace, which can be logged and grouped to become data. While data has always been important to businesses, within the new digital age it has gained both a mass and a granularity on a scale never before imagined. With that has come vastly improved insights. In modern times, reliable data is one of the most important facets of a successful organisation.

Why is data management important to an organisation?

As the breadth and specificity of data that can be gathered has ballooned, so too has its value. This data is invaluable for businesses as it helps them understand their customers’ behaviours, making it easier to understand them, create products for them, sell to them and keep them satisfied.

Data management refers to the collection, storage and use of data as a resource within organisations. There are several disciplines around data management, but all of these stem from the same objective: to help businesses realise more value from their data. 

Data management disciplines include:

  • Data visualisation: Taking data and displaying it graphically through software, to make reporting clearer and easier to understand. 
  • Data optimisation: It’s not enough to have data; it needs to be easy to locate and analyse, clear and accurate, and actionable and useful. Data optimisation looks at all these elements to ensure data is incorporated into your organisation’s day-to-day decision-making.
  • Business intelligence: Using your data to understand the state of play in your industry, and inform critical business decisions using the best evidence at your disposal.
  • Data governance: Ensure your data storage is private and secure, and that your business is fully compliant with data privacy laws.
  • Data warehousing: Collect, deduplicate and cleanse your data, pooling into a single source of truth, for easier usage within the organisation.

What is a data management strategy?

A data management strategy aims to critically consider the best way to handle an organisation’s data, from collection to processing to storage. Typical objectives include ensuring that information is processed, stored and forgotten in a legally compliant manner, that data is stored securely to prevent privacy breaches, and that data is logged and processed in a way that enables accurate analysis and reporting.

Data management strategies are generally led by the IT department. However, ensuring all teams feed in with their informational needs is crucial, helping keep data management relevant to the company’s operations. For example, a chief data officer within the wider company will have a better understanding of what information is needed, and who needs access to that information to enable effective employment. For companies with active citizen developers within their organisation, these non-tech professionals are also a great resource when planning data strategies, as they straddle knowledge of both business needs and technical capabilities.

Data management plans

A data management plan is just that; a blueprint for data management. It lets organisations understand what they need from their data management and help anticipate any upcoming roadblocks, such as security laws between countries, or data warehousing requirements. When undertaking a new project, an effective data management plan should be considered as early as possible, so it can be well integrated within the fabric of your organisation. 

Why is a data management plan necessary?

A good data management plan will map out the whats, whys, hows and wheres of data collation, processing and storage. As part of your plan you should also determine who in the organisation is responsible for the management and security of your company’s data.

Creating a data management plan

Beginning with the objectives behind your data collection, you should be able to work out what data is important to your organisation. Try and anticipate future requirements. For example, a SaaS website may not need location data on customers currently, but it could be useful in future if they expand to new markets. 

Once you have an understanding of the data you need, you should consider the legalities of this data. Personal data is subject to stringent GDPR rules in the UK and EU, while medical data has a high level of compliance still. 

How and where you will collect and store your data generally comes down to what software you are using, and whether it is fit for purpose. If there are many data sources, can these be collated in a format that allows you to analyse across platforms? 

Above are just the broad considerations of a data management plan. However, these are the questions you should be asking yourself if you’re looking to develop a strategy around holding your business information.

Like many things, data management is easy to do, but hard to do well. The flipside of this is that for companies that action excellent data management, it offers significant scope for competitive advantage, enabling clear reporting, smooth operations and informed decision-making.

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