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The Dos and Don’ts of Data Strategy

It is no longer tenable for businesses to sideline data. It is an immensely valuable asset that can provide unprecedented insight into your customer base and market performance. However, with the volume and variety of data accessible at an all-time high, you risk obscuring rather than clarifying these insights if you don’t develop and employ an effective data strategy. Here are some dos and don’ts to keep in mind.

Be honest about what data is useful – and what isn’t

Although data collection and analysis is essential if businesses want to keep up, not all data is equally valuable. The word refers to an ever-increasing array of information, not all of which will be relevant to your sector and business. For data to be an effective source of business intelligence, you need to outline what types of data are not only useful, but usable: if you can’t apply it in a strategic context, it’s useless. Be honest, and ruthless about data – collecting it for its own sake is a costly and ultimately futile exercise.  

Ensure that you’re capable of managing that data

Collecting data without an idea of how it will be managed can be dangerous. A mass of data has the potential to cause huge problems for your IT systems and HR unless you have a plan of where it will be stored, how it can be accessed, and who will be responsible for quantifying and analysing it.

A Chief Data Officer, or equivalent, is responsible for the process of data storage and analysis. They will be able to free up other departments wrangling with data collection on top of their main responsibilities, and codify your company’s data strategy in a set of best practice procedures.

Integrate multiple data streams

Today’s digitised business world moves extremely quickly. Being able to access the right information promptly is crucial if businesses are to make informed, strategic decisions in real time. Having a number of separate data streams across your organisation damages your ability to access this information as and when you need it. As such, it’s an increasingly important facet of data strategy to integrate these data streams – a process increasingly referred to as Master Data Management.

Start by identifying data silos in your organisation, and break them down. This will enable you to identify and eliminate contradictions in your data, and ascertain what is worth retaining. Store the resulting batch of accurate, useful data in an easily accessible location, such as a cloud storage system, which allows users to see updated information wherever they sit in your business.

Don’t neglect the security of your data

Although locating data in a single, accessible source is far more convenient and effective than retaining multiple data silos, it presents a considerable security risk. With all that data in one place, intelligence thieves and fraudsters can deal huge, compromising blows to your business in an instant. Additionally, businesses that experience security breaches can be fined up to £500,000 for failing to comply with the Data Protection Act.

Indeed, cloud systems have been criticised for failing to provide an acceptable level of data protection, so don’t assume they are secure. Ensure that you are aware of cyber security best practice, and never underestimate the importance of securing your data.

Don’t just collect data – analyse it and act on it

Identifying what data is useful and usable is the first step in creating an effective data strategy. It’s of little use, though, unless you make the effort to analyse it and act on the insights it provides.

There are a number of different methods of data analysis, each designed with a specific end in mind. Not all will apply to your business, and taking the wrong approach may well undermine the effort spent in collating a usable body of data. The appropriate method, however, can give you the edge required to gain a competitive advantage in the marketplace; predictive analysis, for instance, can help you to predict future customer behaviour and work on meeting their needs as they arise. Data analysis methods such as this allow the implementation of accurate data-driven marketing that targets customers far more precisely, maximising consumer engagement and spending.

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