Up to 96 per cent of customer contact data is partially inaccurate, according to the Sales and Marketing Institute and D&B. This is a shocking statistic. If you run a business, this figure alone should have you leaping from your seat in panic.
Can your data really be in that bad a state?
The short answer is yes. Over time, data decays at 2 per cent, per month. So your database is never static; it is constantly degrading. Your customers are constantly changing job roles, phone numbers and email addresses. Your business is occasionally adding duplicates, spelling things wrong, and introducing bad data to the database. This situation is costing you money and time, and it’s a needless waste of resources.
It sounds obvious enough when written in black and white, but it’s alarming how many businesses are sitting back and doing nothing about it.
It’s time to change
Data is so critical to business operations that companies are increasingly employing people to watch over it.
A Chief Data Officer is a relatively new role, but it’s been created because there’s a need for someone to give data a voice. This is particularly important at boardroom level, where many stakeholders don’t have full understanding the impact of poor data quality.
Businesses need to stop seeing data as a jumble of characters, and elevate it to the status it deserves. It’s time to give your data credit: it’s a business asset you cannot afford to squander.
So, how is change brought about?
1. Assign the correct ownership to your data
Data quality improvement is not something you can leave with the IT department. It’s not a purely technical issue. It’s not something that can be dealt with in a few days, or a process than can be run to schedule. You need human involvement across the entire business.
To make progress, you need to assign ownership of data quality within the business, led by a CDO, or someone else with influence at boardroom level. This is the first step in a wider culture change that should help people see data differently.
2. Set long term goals for data quality
At DQ Global, we produce software that can process data very quickly, finding thousands of potential errors in a few minutes.
But despite this we can’t purify your data permanently during a one-off data quality project.
For on-going data quality improvement, you need a coherent and complete strategy that runs alongside your normal operations. You need to start with data capture, figure out where the errors are coming from, and put software in place to prevent those errors from being introduced.
You can then move on to using automated processes to catch verification errors and duplicates before they bed in. If someone’s job role changes, you should be able to reflect that quickly and without a great deal of manual intervention.
If you don’t stem the flow of new data errors, a one-off data quality initiative is like pulling the leaves off a weed in your garden. Yes, it solves the problem quite effectively the short term, but unless you tackle the roots, that weed is going to re-grow sooner or later.
3. Join up and integrate your systems
Businesses often struggle with data quality because they store data in so many places. This occurs when businesses can’t get the functionality they need from their CRM, so they start using spreadsheets alongside it.
Sometimes, businesses have legacy systems running on ancient servers, storing data nobody can access. Not only that, legacy systems tend to be isolated, and occasionally, totally unsupported.
If you don’t have an integrated view of a customer, you’ll never fully understand them. You’ll also miss opportunities to sell to them because their profile is broken apart. To make effective decisions, data needs to be out in the open; it needs to be put to work, and systems need to be integrated to support that.
From sales to marketing, budgeting to support, your entire business should be working from a single customer view. You may have to digitally transform certain parts of your system to do this, but the efficiency gains and ROI are always worth the investment.
4. Enhance clean data from third party sources
If you rely completely on your own data, you’re going to miss opportunities, and leave the market wide open for your competitors.
But if you plug your data into a third party enhancement service, it can be enriched with information that gives you an edge.
A couple of weeks ago, I wrote a guest blog for KiteDesk about the importance of data enhancement in CRM which goes into this in more detail.
When you change, you can achieve
Data quality assessment is made up of three key components: accuracy, completeness and timeliness. These three components never come together through chance. In order to maintain ROI, you’re going to have to invest in change.
Change is becoming more important as marketing evolves. Social media is inspiring new ways of talking to people, and better ways to advertise and connect. For example, marketers are increasingly looking at hyper-personalisation and highly tailored messaging, using online ads and social conversations. You simply cannot personalise your marketing message without knowing who you’re talking to. Your data is the missing link.
Now, too, Big Data is upon us. The Internet of Things is increasing the rate of data acquisition. We are moving towards a real time business environment; 25 per cent of businesses now have Big Data projects in production. Customers don’t just expect you to make good, accurate decisions. They expect you to use their data to make those decisions near-instantly. If you’re leaving data quality purely to chance, you’re walking a very treacherous path, because you can’t offer the focus and timeliness your competitors are offering.
It’s time for your business to stop leaving things to chance, and prepare itself for change. We can’t promise that it will be easy, but without change, you simply won’t have the insight to compete.
About DQ Global
Armed with qualifications in mechanical engineering, business and finance, and experience of running engineering and CRM businesses, Martin founded a successful CRM (Customer Relationship Management) software house in 1992, supplying systems to large, medium and small sized companies. Developing a deep understanding of the value of data, he became concerned that many organisations were making decisions based on poor quality data. To fill this gap in the market, he sold the CRM company and started DQ Global in 2002 to provide data quality solutions, with a mission to detect, correct and prevent data defects which undermine business decisions. Since then, DQ Global has become a global market leader, delivering enterprise-wide data solutions utilising leading edge technology. Martin has gained a wealth of knowledge and experience and has established himself as a Data Quality Improvement Evangelist and an industry expert.