Data quality should underpin all business decisions

By Stuart Johnston, UK Managing Director, Experian QAS.

Data in its raw form can mean very little until it is processed and analysed into tangible information. If exploited effectively, data can be the one of the main business drivers within any organisation, providing the source on which to base many business decisions. At QAS, we recently undertook some research that revealed that there are, on average, more than 96 different entry points for customer data to enter any one business. No surprise then that it is absolutely crucial that organisations are clear on not only how and where data enters their business, but how to harness it in order to remain competitive.

“Managing contact data is a bit like painting the Forth Bridge – the process is never finished. Customer data is always changing. Treat it as such and the process of building a data quality strategy becomes infinitely easier.”
-Stuart Johnston

Complete, accurate, and reliable data is powerful in many ways.  By segmenting it, you can use it to view historical patterns and understand how your customers spending habits have changed over time. You can observe current behaviour in real time and make on the spot, more informed decisions as a result and you can use the information to help you predict future customer behaviour and activity. 

Garnering great information from the data you hold can seem like a daunting task.  How do you build an effective strategy that ensures the data held in your business is turned into relevant, useful and tangible information? In my experience, a multifaceted approach is one that often reaps the greatest results and return on investment.  Below are a few simple steps that I recommend form part of your consideration for building a data quality strategy.

Start at the end

When you evaluate data quality, start at the end.  Think about the overall objectives of your organisation and the data required to meet those objectives.  This will impact on the amount and type of data you need.  Don't waste time collecting and storing information you won't use. Have a clear sense of what you are aiming to do. 

Consider the data elements

Evaluate the data you already have and decide upon its relevance.  Analysing your current data should indicate where you have gaps and what additional data is needed.  Key, is thinking about everything you might want to know about a customer or prospect, so that you can ensure this information is collected and inputted into your data systems and processes from day one, even if the data itself is accumulated over months or years of ongoing customer communications.

Measure data quality

It is essential that you have a way of measuring the quality of the data over time.  Even the most robust systems and processes to capture data will need to be reviewed on an ongoing basis. 

How to get to where you want to be

Benchmarking is a key component.  A workable data quality strategy should allow you to examine where you are now, where you would like to be at a given point in time, and then assess your performance against those targets.  If it is too much to tackle all at once, identify the areas that are having the biggest negative impact on the business, and prioritise those. 

How to win support for the investment

Like any investment, a good data quality strategy needs to be justified to those holding the purse strings.  Connecting the proposed investment to the company objectives around reputation, revenue, cost, profit, compliance should act as a good business case for investment.

And tell everyone about it - all the way up the line to gain management support and all the way down the line to ensure its importance touches everybody.  Creating a culture where data quality can flourish isn't easy.  Making it a part of everybody's work commitment is a step closer.

Start again

Revisit your initial objectives to see how your results are improving, review the process regularly and make sure the key stakeholders are kept fully informed of performance.  Data quality can't be left to look after itself; it simply doesn't work like that.

Finally, consider who needs to be involved in your data strategy, both in terms of creating it and implementing it long term.  Who within your organisation will set the targets and who will make sure the targets are being met?  Typically I'd recommend the responsibility of developing and managing the data strategy is the leader of the team that uses the data the most, for example, the marketing manager.  Sounds obvious, but you would be surprised at the disconnect we see between the data owner and user which often leads to an ineffective data strategy in place. 

Every business has the opportunity to use its data assets more efficiently and building a data quality strategy is a good place to start.  Managing contact data is a bit like painting the Forth Bridge - the process is never finished.  Customer data is always changing.  Treat it as such and the managing the data strategy becomes infinitely easier. 

On a final note, I cannot stress enough the importance of promoting data quality throughout your business, building it into your culture.  Celebrate and praise great examples of data processes or usage to support decision making but also, highlight bad examples and misuse of data in a constructive manner.  A business often isn't a business without its data - make sure you're giving it the attention it deserves. 

For further information visit our "Building a data strategy" webpage, where you can download useful guides, videos and webinars.

For more useful data statistics, visit www.qas.co.uk/useful-statistics.