Poor data quality causes companies to lose up to 30% of their turnover

An interview with Benjamin Protais, digital transformer

Published in

Alliance Data

4 min readSep 12, 2020

Benjamin Protais, Consulting Director at Business&Decision

Benjamin Protais is the Consulting Director of Business&Decision in Geneva, a firm specializing in data management and digital transformation. He advises SMEs and larger companies in Switzerland as well as in Europe. After studying biochemistry, he trained in information systems management by making his own transformation.

“Companies lose 15% to 30% of their turnover because of the poor quality of their data”

This somewhat provocative quote, validated by trustworthy sources (IBM [1], Salesforce [2], Gartner [3], Forrester [4]), often makes impression. Companies usually refute this statement, while being unable to prove the opposite. And that is where the magic of Benjamin comes in: he can support decision-makers in factualizing their current situation and measures the loss of value realized on an annual basis.

A step-by-step strategy

No digital transformation without data. To turn it into a competitive advantage, a business holder must transform data into a service added to the existing model. To this extend, taking care of your data (clean, maintain and use) after defining your purpose will be mandatory. In other words, how is your professional activity concerned by data enhancement? Three obvious answers to this question. Data will enable you to:

Sell more of your current product range
Sell new products or services
Reduce costs, save money and thus make a better profit

Once your goal has been defined, you need to investigate the direction to take. For instance, a lever to sell is to send more tailor-made emails to customers. You would therefore go and see the customer file to measure the factual value of the information it contains: what information is stored, and for each piece of information, what are the associated quality indicators (does the customer file contain the requested information for personalization? Does it contain duplications? Is the customer file split up in several company departments or centralized?). Only then could you define a factual value allowing to measure and monitor the quality of your customer file. This value will then be improved, step by step, in order to reach the set objective.

In contrast to the quality of a process, the quality of data - generated as a result of a process - is harder to apprehend because it is invisible, intangible. And this is where the ‘hidden’ (or rather ‘invisible’) costs of the company lie.

Data engineering is an approach to designing and developing information systems

The customer database, the most concrete case

After having advised dozens of companies in their transformation, Benjamin notes that widespread habits often come up as obvious cases of poor data management. The first thing to start with is the management of customer and partner data. The second concerns the company’s product data.

Indeed, data must be well collected first, then structured and finally used following best practices. An example of mismanagement comes out when the accounting department handles a customer database containing physical billing addresses and the marketing uses its database containing email addresses.

A crisper case occurs with poor product data management. As recently as January of this year, a Casino hypermarket in France was selling a 55-inch TV set at 30.99 euros instead of 430.99 euros, causing a huge crowd in the shop until late in the evening [5]. It was probably a mistake in the management of the product sheet, the number 4 having been dropped at one point or another. This silly mistake caused costs, wasted time and gave the shop a bad brand image, all because of poor data management. Such a misadventure also happened to the Swiss online shop Digitec/Galaxus in 2018 [6].

Another example of poor management with sensitive data repositories: we often hear cases of data leaks (i.e. customers’ bank card numbers, email lists, etc.). This type of leakage generally costs a company not only money, but also its reputation and the trust of its customers.

Photo by ThisIsEngineering

Sources:

Poor data quality causes companies to lose up to 30% of their turnover

An interview with Benjamin Protais, digital transformer

“Companies lose 15% to 30% of their turnover because of the poor quality of their data”

A step-by-step strategy

The customer database, the most concrete case

Written by Jacky Casas