The time has come for the digital transformation of companies. Data has become pivotal for all company activities. It will steer marketing activities while feeding sales representatives with prospects and opportunities. Follow these 10 rules to ensure that your data strategy is the winning strategy.

1. Give your CDO power

Today, breaking down the silo mentality is the top issue for large organisations as well as for SMEs. It takes diplomacy and dialogue to get the marketing and sales departments to share their data. Although the CDO (Chief Data Officer) position appeared only a few years ago, it is important that this post should have real power within an organisation. Authority and coercive power are often necessary when it comes to successfully completing projects and breaking down barriers. In order to achieve the digital transformation of the company, it is vital to have a direct line of report to general management and the support of the executive committee.

2. No data without governance

Moving into the data age does not just mean rolling out new-generation databases and acquiring Big Data tools. The effort can only be long-lasting if the rollout of tools goes hand in hand with the implementation of an organisation. And the effort has to go much further than simply creating a CDO position. The IT department and all business areas must be made responsible with regard to the quality of the data that are to supply the tools. Each business unit must be fully involved in data governance; this is the only way to ensure the long-term success of a data strategy.

3. Hire Data Scientists

This is a key point in a company’s digital transformation. A company that wishes to put data at the heart of its business model cannot merely use Data Scientists on an ad hoc basis to develop a model. Nor can it be content with the predictive functions bundled into analytical tools. The limitations of these approaches will quickly become apparent. A data strategy is not a sprint but a marathon. It is necessary to invest in an internal team who will improve not only their skills with the tools but also their understanding of the company’s business. Data Scientists are rare and expensive, but you need them!

4. Do not make do with the most obvious data

Being content with data drawn from Web Analytics and with what the sales representatives have entered into the CRM represents only the tip of client information. Making do with the most accessible data sources can lead to very detrimental errors of interpretation, as is often the case with the last-click approach. The traffic that Google generates to an e-commerce site is certainly vital, but is Google the only source of the sales? As soon as we want to go beyond the most superficial information, we need to take an interest in more data sources and we need to know how to obtain the data, integrate it and correlate it with other available data.

5. Implement a DMP as a priority

Today, all marketing departments are struggling with the difficulty of reconstructing their clients’ trail — a trail that is often punctuated by return trips between digital media, sales points, etc. However, being able to reconstruct these trails is critical, if only in terms of attribution. Which medium, which marketing lever has been essential in finishing a sale? The implementation of a DMP (Data Management Platform) enables us to get as close as possible to reality. It’s the key to enabling the best ROI calculation of campaigns.


6. Forget Excel!

For years, Microsoft Excel has been the favoured tool for both marketing departments and sales representatives. There’s nothing better for quickly creating an activity summary dashboard, or setting up a pivot table to do some simple analyses. However, this approach results in harmful effects. Everybody has their own data and only shares it from time to time. Nobody is working on the same data anymore and this is a source of frequent disagreement. Finally, as far as advanced visualisation and data analysis are concerned, the Excel tools are insufficient for today’s challenges.

7. Share information

For many companies, the image of the marketing department comparing its figures with those of the sales department at every meeting is no cliché. A systematic waste of time and a source of endless internal conflicts, the lack of information sharing and internal collaboration undermines efficiency in companies. Although these departments have become used to providing regular reporting to their general management, they must now learn to set up shared dashboards and KPIs. This is crucial in order to be able to assess the real impact of marketing campaigns on sales.

8. Pay attention to old habits

Big Data is shaking up certain old habits. For years now, the IT department’s data warehouse experts have been used to structuring data and organising it so as to optimise storage volumes and performances (from access to analysis). Facing them is the new school, which wants a maximum amount of data to be kept since storage space has a very low cost, even the data which doesn’t initially seem useful. As for processing power, the Cloud makes this available at a low price and virtually infinite. One has to know how to draw the best from these two worlds so as to maintain the agility of Big Data while being able to industrialise IT processes when necessary.

9. Innovate differently

In many markets, innovation cycles are accelerating and, very often, start-ups are faster and more agile than conventional companies when it comes to imagining disruptive products or new uses. Revamping a company’s data strategy represents an opportunity to imagine innovation in a different way. It’s an opportunity to open up to start-ups via approaches such as Open Innovation, the organisation of hackathons, etc. Likewise, an Open Data strategy represents the opportunity to bring about new business models and to create an ecosystem of partners around one’s product offering.

10. Think about the future, think predictive tools

According to the latest EBG/Qlik barometer on the digital transformation of French companies, around a third of sales departments think that the sales forecasts that they have are good. The bulk of the analysis on which they have to base their decisions focuses on past activity. This is valuable information but doesn’t necessarily properly shed light on what must be done. We should no longer make do with extending the curves and should, instead, put real predictive tools in place. It is at this price that we will be able to anticipate future changes, exploit emerging market niches, and disengage before our competitors from the markets that are likely to slow down.