We invited Clemence Laguette, Chief Data Officer, Engie to share her thoughts on “Creating Value From Data" at our recent Data ROI event. You can watch her full session here or read on for a few highlights.

Data and analytics initiatives impact a lot more than just the bottom line. As Clemence explains, “when we talk about valuation, it's not only about financial valuation, it's also to make sure that it's going to bring something to the employees, the business, your customers and does so with minimal environmental impact.”

Here’s a look at Engie’s 3 P’s for determining the value and cost of data. 

People

When it comes to the human element, there are two sides of the coin: employees and customers. For each group you should be looking at 3 key elements: experience, privacy and costs.

Data and analytics can have a profound impact on the employee experience, both in good ways and bad. To start, ambitious, complex data science projects can be incredibly difficult and time consuming. Ensuring that these projects are worth the trouble is essential to avoiding employee burnout and frustration. 

Secondly, if a project requires additional training to execute, the cost of reskilling must be included in your data ROI framework.

During the early stages of planning it’s paramount that you establish clear objectives for what you want the data project to achieve in terms of how it will benefit employees and customers.  In addition, outlining how you will measure success in this area and what metrics will be utilized to do so will help ensure the project stays on track and delivers its intended outcomes. 

Another area that is often overlooked is data privacy. If you are using personally identifiable information, it’s critical that you are as conservative as possible in terms of the volume of data you're using. This will help reduce risk of data leakage. 

Planet

As Engie specializes in low-carbon energy, minimizing the environmental impact of its data footprint is a top priority. In addition, even for those who might not be directly involved in the world of sustainability, environmental impact metrics can help organizations ensure that their data science projects are efficient, streamlined and elegantly executed. 

As Clemence explains, “We’ve embraced eco design, which means that we don't try to include as many features as possible, only the essentials to ensure we get the results we want. 

We understand that these key features are enough, because most of the time, when we put in everything that we imagined, many of these features never end up getting used. So these models consume a lot and, because they tend to be more complex, are not user-friendly, and it's very difficult to then increase or scale up or to apply it, to make it communicate with other software. Not only does it reduce the overall value of the project, it can also be costly as it consumes so many resources.”

Clemence also cautions against collecting too much data as it will not only increase your carbon footprint, but expands your organization’s attack surface. 

Prosperity

Determining data ROI really boils down to understanding risk. As Clemence explains, “it's not only storage, it's all the tools they are offering you to analyze this data. And so then you need to pay a lot to analyze your own data.

So it's a lot of investment, even like financial investment to reach this stage. So you have to understand and balance which risks you're taking, like financial risks, cyber risks, people risk, because then you also exhaust people and resources by accumulating data and sending too much information, notifications, too much training as well.” 

This is why measurement is key. Afterall, you can’t change what you can’t measure. 

WANT TO LEARN MORE?

Register For The Data ROI Virtual Event To Watch Clemence’s Full Session On-Demand