Apr 2020 | Data Quality | Risk Analytics
By Posted by Mark Wright

Every conversation I have involves data

Whether that’s finding additional insight into customers, business operations to streamline processes, or digital transformation programmes. Operators are investing in data to maximise their competitive advantage in a saturated marketplace1, while at the same time responding to customer and regulator demands on fairness and transparency. I was at a conference several years ago listening to an operator say that if they could increase their connection rate for new customers by 1% it would translate into £400m of additional revenue. What the actual number is now can be debated, however, what is definite is that data is at the heart of every decision and it can have a significant impact to both business performance and how customers are treated.

However, globally most organisations don’t see themselves as being data driven despite the increasing investment in data and analytics. Our research2 shows that whilst organisations are advancing there is still a disconnect due to; a degree of distrust in data, data accuracy and a data skills shortage. Not understanding how the data got there, how accurate it is and when it is useful not only adds to the level of distrust but also results in organisations not maximising the value from the investment made. For Telco operators, this not only relates to better customer decision-making and competitive advantage but to the monetisation of the wealth of mobile data they hold.

Data is growing exponentially, with the number of data sources and complexity increasing. Advanced analytics through machine learning are starting to be trialled and proved in areas of credit risk and fraud identification, and there is an expectation that AI will have the biggest effect in customer service and retention areas according to a recent white paper by Finextra3. However, on average organisations believe 28% of their customer and prospect data is suspected to be inaccurate in some way, with only half (51%) of organisations considering the current state of their CRM/ERP data to be clean and can fully leverage it4.

So, what does this mean to both you and your customers?

Inaccurate data results in organisations wasting resources and incurring additional cost, sub-optimal analytics means business outcomes are not maximised and customers don’t get the best experience. A simple example of the benefits of high-quality data surrounds the process for the regular provision of data to the credit bureaux. An underlying principle for all credit bureaux is that the data provided by organisations needs to be of an acceptable level of quality. Where records don’t satisfy these validation checks they are returned to the supplying organisation for investigation and correction. I was recently speaking to someone who manages this process and it takes an average of three people, four working days per month to do this. What other value generating activities could they be doing with this time if the data in their source systems was accurate?

Reaching and maintaining 100% data accuracy is unlikely, but it is possible to come close and something we should all be aiming for.

The opening sentence in the recent Ofcom Policy Statement on Fairness for Customers5 starts: “Ensuring fairness for customers is a continuing priority for Ofcom …”. The fairness framework covers all aspects of the customer experience, from treatment throughout the customer journey, price discrimination, is anyone being harmed, through to does a service require risky investment. This builds on whether customers can get a fair and appropriate deal at the end of their contract following the introduction of end-of-contract notifications (ECNs) and annual best tariff advice in February 20206.

What I find interesting is that there is acknowledgement that fairness can still be a concern in a competitive environment – and the UK Telco market is certainly competitive! Ofcom goes onto say that “The ability of providers to exploit customers is likely to increase as data capture and data analytics advance, creating potential for increased price discrimination.”7 However, there is a balanced recognition that price discrimination can result in positive outcomes for different customers, for example, being able to identify and provide lower prices for customers who would otherwise not be able to afford it. With the average out-of-contract versus new customer price difference being £9-£10 per month, and the average out-of-contract vs. re-contracted customer price difference being £8-£9 per month, the harm to customers is significant8.

If you don’t trust your data and it is not accurate, how can you confidently ensure you are treating customers fairly? Ofcom research from UK operators states that out of nearly 9 million out-of-contract customers, 1.5 million of these are vulnerable9. While some of these customers will be paying more than non-vulnerable customers it is not all about price. The ability to accurately capture, differentiate and subsequently provide appropriate treatment for vulnerable customers is key. For example, accessible format communication for customers with disabilities, or where customers rely on communication services due to disability or illness and can’t leave their house.

Vulnerability is another subject altogether. When you do classify a customer as vulnerable what do you do with the information? Do you make sure this is accurately transferred to all other relevant systems? What happens if a customer’s circumstances change over time? And of course, just because a customer is identified as vulnerable doesn’t mean they can’t afford to pay you.

Large scale data projects, enterprise-wide master data management initiatives to deliver a single customer view for customer experience can have their challenges and bring with it risk. What happens if scope changes, new applications and websites developed, mergers happen and so on? These long-term initiatives do need to take place, but at the same time it is important to quickly build trust in data. Look to identify a few quick wins and demonstrate the value of data improvement. What would be the impact on retention rates and revenue of being able to better identify existing customers applying for additional products or services? Improvements to marketing address data quality would result in more accurate profiling of prospects – how long would it take to trail this on a segment of prospects and demonstrate the improvement in net conversion rate back to the business?

Trust in your data can be built by showing the business its true value. Don’t just look at standard management information (MI) measures such as completeness statistics, show how high-quality data can support meaningful outcomes and improved business performance.

To read the new 2020 Global data management Report in full, simply click here.

Sources:

  1. In 2019 Q3: Mobile subscribers totalled 84.91m and declining ARPU to £17.03 for post-pay contract (as compared to £18.12 in 2018 Q3). OFCOM Telecommunications Market Data Update Q3 2019, 30 January 2020
  2. Experian 2020 Global Data Management Report – https://www.edq.com/resources/data-management-whitepapers/2020-Global-data-management-research/
  3. “AI and information paving the path to personalisation”, A White Paper from Finextra in association with Opentext, January 2020
  4. Experian 2020 Global Data Management Report – https://www.edq.com/resources/data-management-whitepapers/2020-Global-data-management-research/
  5. OFCOM, “Making communications markets work well for customers”, 23 January 2020
  6. OFCOM, 15 May 2019, “Helping customers get better deals: Statement on end-of-contract notifications and annual best tariff information”
  7. OFCOM, “Making communications markets work well for customers”, 23 January 2020, section 2.4
  8. OFCOM, “Making communications markets work well for customers”, 23 January 2020, page 31
  9. OFCOM, “Making communications markets work well for customers”, 23 January 2020, page 30