Are You Still in the Dark About the Quality of Your Data?

More and more businesses are waking up to the threat of poor data quality. Were gradually seeing the risk being taken more seriously as the shockwaves of poor management are felt.

Yet for many businesses, data quality is seen as an abstract concept; difficult to understand, and impossible to value.

When the business formulates its budgets for the year, data quality is often skipped over, because nobody really knows whats wrong. Sure: they can see emails bouncing, and their customers are drifting away to competitors, but the root cause hasnt been fully determined.

These businesses arent deliberately neglecting data. They just dont realise how important it is. In fact, its the most critical asset that your business currently holds. As your competitors start to take action on data, your business is at risk of losing momentum.

Why Data Matters

As a society, we are now fully connected. We are reliant on the systems that bind us together. Collectively, humans are generating more data in a day than they have in many thousands of years.

Its widely accepted that data decays at a rate of 2 per cent, per month, regardless of how it is stored. So, assuming you are not taking any action to prevent this, your data is slowly and quietly becoming less useful. Today, its less accurate and less valuable than it was yesterday, and its considerably less valuable than it was last year. You might not see this as an emergency, since you dont really need to access that data right this second. But when you do, the state of your data could catch you unawares.

Consider a situation where your business embarks on a new marketing campaign. It sends out email marketing messages, and it creates a marketing letter to send out to prospective buyers. After investing several weeks curating content and planning the launch, it finds that its emails are bouncing back in their hundreds. And worse, once the direct mail is sent out, a huge amount comes back as undelivered: fit only for the recycling truck.

This is a very simple example of the cost of poor data quality for just one department of your business. Yet one inaccurate record is going to impact on every department, given time. Once a record goes out of date, that record is effectively useless, and any attempt to use it is simply a waste of resource.

Shedding a Little Light

Once you reveal the extent of your data quality problems, there are two costs to face up to:

• Youre going to need to deal with the state of your existing data, which means merging duplicate records, removing errors, and making data fit for purpose. This usually involves a period of data review and purification, which can be made substantially easier with data quality software.
• Theres going to have to be an on-going focus on data quality, in order to capture any new errors that will inevitably be introduced. As weve learned, a degree of data decay is an inevitable and pernicious process, and theres also a risk that errors will be introduced by your staff, or the systems you use.

Some businesses also go one step further than these two steps. They appoint a Chief Data Officer to take charge. The primary purpose of this new role is to give data a more prominent position in the business. This can help to ensure that data quality is given the focus that it deserves, and it can help to inspire the vital culture change that will prevent wide-scale data problems in future.

After all, data can only improve if action is taken at the boardroom level first.

Taking Action

Data quality software should form the cornerstone of your organisations data quality drive. Even the smallest company cannot realistically make any meaningful progress without some kind of automation.

With data quality software, you can cleanse data in-house, without the need to send data to an external bureau, maintaining privacy, integrity and business continutity. Many tools integrate directly with CRMs systems, and its possible to integrate data quality checks into a wide range of commercial and bespoke applications.

Even something simple, such as data quality checks within a form, can be enough to stop errors from being introduced at all, which can have a considerable effect on the overall health of your CMS or other data silos. Once you are checking data at the point of entry, you can stop people from creating duplicates automatically; you can also prevent basic form field errors that can wreak havoc across your integrated business systems.

Conclusion

If you havent yet discovered the extent of data quality problems within your business, its impossible to make plans to resolve them. Many businesses are still in the dark. But we know for a fact that inaction will lead to disaster. Weve seen it happen in many businesses already.

If data quality is allowed to decline, your customers will lose trust in your brand. Youre going to alienate people that might have spent a lot of money with you, because you havent invested in maintaining their data. Worse, you may lose touch with the leads that you invested so much in acquiring. The reports and analysis that you rely on to grow the business will be flawed, and subject to considerable margins of error.

Factor in the waste, too: every time you assign a budget to marketing and sales, and asking them to use faulty data as the basis for their work, you are assigning a proportion of that budget, quite literally, to the trash can.

But all is not lost. Poor data quality is not inevitable. And there is time to come out of the dark and into the light. With the right data quality software, and a change in culture, you can set a new course for your data starting now.