Looking to Digitally Transform Your Business? Start with Data Quality.
Looking to Digitally Transform Your Business? Start with Data Quality.
?The digital transformation is underway now that all businesses, in particular, those associated with customer relationships, have become aware of the value that data could add to their operating activities. However, the divide between top performers and others continues to grow, with the latter only experiencing a fraction of the potential the digital economy could offer them. The most frequently mentioned causes range from a lack of management support to the difficulty in recruiting experts in data science or the absence of a culture of experimentation. What is often overlooked as a reason for not taking full advantage of data is issues related to data quality. Yet, in this regard, the figures speak for themselves.
Is unreliable data inevitable?
Several studies show that one-fourth of the contact details contained in corporate customer databases are incorrect. This is explained in part by the fact that they are rather volatile: 71% of these data have been changed at least once over the course of the last 12 months (i.e. based on a move, change of phone number, change of position, role, or situation, etc.). Result: 54% of companies admit they do not have the data necessary to personalize their content. New initiatives, such as those linked to Big Data are also affected since we observe that 80% of data experts', such as data scientists or data analysis, time is taken up preparing and cleaning data (on average 2 hours a day for a data scientist).
Should we consider handing responsibility over to a central governance service, possibly outsourcing the necessary tasks, as we do with janitorial or security services? Or, rather, is now the right time to take the bull by the horns and take back control of what has now become the fuel of marketing campaigns, sales and customer loyalty activities: customer data?
And what if we cleaned up our data?
Everything points to now being the right time. If it seemed reasonable to use central services for any activity linked to customer data, then it was when these were under the control of a few specialists and concentrated in a handful of systems like CRM, data warehousing, or EPP. But not now that digital marketing, Cloud applications, and self-service business intelligence have brought the data from our operating activities closer and make marketing teams much more independent in the management of their data (not to mention being responsible for its proliferation).
It is therefore high time for those handling customer data on a daily basis to participate in the maintenance of its quality. All the more so since we're seeing new self-service tools emerge to make this task easier. The better solutions are equipped with familiar man-machine interfaces like Excel that make them accessible to non-experts; they are capable of automatically recognizing the most common customer data such as e-mail addresses, phone numbers or postal addresses, and guiding users towards the necessary actions to correct the data that appear suspect. These tools bring with them collaborative features allowing marketing to orchestrate data quality enhancement by assigning tasks to those most likely to perform them. They can also automate tasks; for example, verifying the validity of addresses, telephone numbers and e-mail addresses, or even enable the merging of duplicates. Better yet, automation tools can learn based on human know-how by taking advantage of technologies, such as machine learning, to understand the rules of reconciliation as performed manually by experts, then re-using them on a large scale on much bigger data volumes.
Ultimately, these types of tools allow marketing teams to roll up their sleeves and organize campaigns to enhance their data. They are also the primary beneficiaries since the objective of these campaigns is also to improve the conversion rate and the effectiveness of marketing campaigns.
One for all and all for one
Big Data, but also the Cloud and self-service, pit companies against the same challenges. It is time to establish a more collaborative governance model by making everyone responsible for managing the information capital of their companies. This does not mean that the centralized governance model has to disappear. But it is becoming more the exception than the rule, as those who use the data are the best placed to guarantee its quality. Most often, they don't even have a choice because no one will do it for them! That rare bird that will solve the problem of data quality doesn't exist. The entire challenge, as we see it, lies in the establishment of a governance system which, rather than seeing itself as the data police, makes it possible to approach the problem and find solutions collectively. And that is exactly what the digital world offers us today: One for all and all for one!