How’s your data health? Pretty bad, if you’re honest. Here’s why and how it needs to be fixed to realise the benefits of the data revolution.
All businesses have long recognised that the more data about their customers they are able to gather, the better they can understand and then service them. Customer data has the potential to drive new growth and enable businesses to increase customer loyalty.
The story was that the data revolution was going to fundamentally change the relationship between customers and brands. Using data, companies would be able to offer personalised engagements and offers at scale, leading to bigger deals that were closed more quickly.
When combined with increasingly sophisticated algorithms, data-savvy companies would be able to offer customers what they wanted at a specific moment, almost before they even realised what it was they did want.
In short, it seemed as though the data revolution was going to finally deliver the Holy Grail of business: a single, complete view of the customer.
Developing a supportive culture is particularly important and difficult to get right.
Unfortunately, the promise hasn’t quite been realised. In fact, according to McKinsey research, a whopping 77% of organisations reported that customer insights simply have not delivered the growth and competitive differentiation so longed for.
Why the gap between aspiration and reality?
The first point to make is that in order to realise the data dividend, companies had to become fully digital. The trouble is that most organisations treated this digital transformation as nothing more than a perfunctory box-ticking exercise, something that everyone else was doing.
By contrast, to realise the benefits of the data revolution and achieve the desired 360-degree view of the customer, we need to revolutionise how we think about and approach customer data. Only companies that adopt a holistic perspective and treat data as a strategic asset that underpins every decision, will thrive.
Healthy businesses, in other words, will be the ones which prioritise data health.
Understanding data health
Just like any biological organism, an organisation is made of interdependent systems. In the body, these systems include the circulatory, immune, respiratory and digestive systems, among others. Similarly, organisations rely on interdependent functional groups: marketing, HR, sales, finance, strategy and so on.
What ties these functional groups together is data. Data is key to understanding what is going on in the business, and also acts as an essential diagnostic tool when things are running badly. It is, therefore, imperative that the company’s data is healthy − that is, up-to-date, accurate and accessible − and can thus be used to support effective, timely decisions and help achieve business objectives.
So, how to ensure data health? The short answer is that there is no silver bullet. The business environment is complex and constantly changing − and that means the challenges faced in keeping a company’s data healthy are similarly in flux. Rather, companies need to treat data health as a discipline that incorporates all three dimensions of it:
Preventative measures: Identify and resolve data challenges before they become an issue.
Effective treatments: Systematically improve data reliability and reduce risk.
Supportive culture: Establish an organisational discipline around data care and maintenance.
Developing a supportive culture is particularly important and difficult to get right; the broader point is that data health is more complex than just ensuring data quality is improved.
New data is being generated all the time − and in astonishing and growing volumes. This means the process of fixing data is not a one-time activity but a continuous one that needs to be integrated into how the organisation operates.
Scoping the challenge
Before looking at how to improve the quality of data and so build trust in it, you would do well to remind yourself of the difficulties of this task.
In parallel with the growing realisation of data’s value comes the realisation that it presents significant challenges. Among them are:
An increasingly complex data environment: Internal and external sources of data are proliferating, and the volumes of data being generated are staggering. An organisation can find itself dealing with 400 or even more different data sources, all producing data in varying formats.
The sheer volume of data compounds the complexity. The figures are so large they can be hard to comprehend, but perhaps the one that best captures the reality is that 90% of the world’s data was generated in the last two years, with 2023’s volumes set to increase by over 150% by 2025.
Increasing demand for data across organisations: Ninety-nine percent of companies recognise that data is crucial for success, yet 97% face challenges in using it successfully, according to the Talend Data Health Barometer 2022.
Stringent data privacy regulations: Because so much of the data is sensitive, regulators continue to implement strict controls. South Africa’s Protection of Personal Information Act mirrors the European Union’s General Data Protection Regulation. Both specify significant penalties, and the number of fines issued by European regulators is on the rise, with a sevenfold increase in the EU in 2021.
Data professionals are scarce: Professionals who have the skills to make sense of all this data, and provide insight into individual and consumer behaviour, are much in demand. Very specific skills, many of them based in mathematics, are required, ensuring these individuals will always be at a premium. They are, therefore, constantly receiving new offers from recruiters.
In my second Industry Insight article, I will look at the question of data quality: why it’s so important and how to achieve healthy data.
Written by: Louis De Gouveia, data competency manager at iOCO.
Originally featured in ITWeb
