with Penelope Bellegarde
Cora has been named in the 2022 Gartner® Magic Quadrant™ for Strategic Portfolio Management. Get complimentary access here
Cora has been named in the 2022 Gartner® Magic Quadrant™ for Strategic Portfolio Management. Get complimentary access here
with Penelope Bellegarde
Penelope has specialized in the area for 14 years and one of her missions is to try and combine digital analytics with artificial intelligence.
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Absolutely. So, the field of digital analytics broadly consists of analyzing consumer behavior across digital platforms. Whether that is websites, social media platforms, but also assessing the effectiveness of digital marketing campaigns. And by the way, this is something that applies across sectors.
So, I’ve been involved over the years, working with media companies, travel, e-commerce, professional services, banking, including the public sector, as well. It is not just about making more money online. It is also about how can we use digital techniques to save costs and in the case of the public sector, for example, it’s about how digital can help us reduce costs to serve, for example. So, it’s got very broad applications, which is why it’s a fascinating industry.
One thing that’s really, really important is understanding what it is we want to achieve with data and why do I say that? Well, in the digital world we have sometimes, I say that we have far too much data we have a lot of data that is being collected because it technically can be, not because it should. And one of the drawbacks of this is that we end up with organizations, especially large ones, public and private, who end up with tons and tons of data that they are not sure what to do and not sure how to leverage properly.
And they are also not sure about what data actually really matters. And so one of the things that I spend a lot of time helping clients with is identifying the data that really matters for the objective that they want to achieve. And we do that through the identification of KPIs – key performance indicators. And this is useful because it’s better that we go from 200 different data metrics to five or 10 maximum. And these are the beginnings of the answers to the questions that we need to solve for organizations.
It’s an interesting question because I get that question a lot, but it’s very specific to organizations because it’s very specific to what they want to achieve. And even if we talked to two different companies in the same market, let’s say, two different banks, for example, or two different fashion companies, they may well have very different KPIs because the objectives that they’ve set themselves are very different, the customers that they serve may be very different.
And so, even though it can be tempting to rely on the top three or the top 10 KPIs, I would say sometimes it’s a little bit dangerous because KPIs are so specific to one organization and its strategy before we get to identifying KPIs, there’s actually a lot of work that needs to be done, which in many cases isn’t done. This is why many organizations end up with data DOIs, as opposed to data insights. So of course, for example, in the e-commerce world and banking world, which are two sectors that I have been involved in over the years, there are KPIs that do tend to come back into vogue.
But I want to be careful here because I think that looking at mainstream KPIs is sometimes part of the problem for organizations. It’s the $1 million question that sometimes cannot be answered without actually really bringing in key stakeholders in each organization and then defining the key questions they need to answer. What’s the value that we want to bring? And then, let’s review all the data that we’ve got and select the data that matters.
That’s true. Absolutely, and yes. So, education around data is something that I’m hugely passionate about. I find it really rewarding when I can help demystify the whole data piece to organizations that really need it. And the other thing is data isn’t just for the techies anymore. It may have been the case 10 years ago, but now everyone is expected to not only consume data but to actually be in a position to act upon it. And it’s really important to be able to give some simple techniques and methodologies to anyone in the organization so that they feel comfortable acting upon that data.
And this is something that I try and do as much as possible. So I spend a lot of time designing data programs, which are, as practical as possible, really about making sure that by the end of training individuals, they are actually able to start really understanding their data with confidence, because I think there are many people who are still very scared of data. They’re not really sure how to tackle the whole piece when actually it doesn’t have to be that scary. If you follow the right methodology it can be accessible to everybody and I think that’s really important.
My number one tip, and something that I really insist on during training programs, is that we have to start with asking ourselves: What it is that we want to solve? What it is that we want to ask? So, spending time on really identifying a very good business question is absolutely critical and the reason for this is, it is a number of things. First of all, it is actually telling us where are we going? Where do we need to be by the end of this exercise?
We need to have answered this question. We can’t afford to just look at data because it’s interesting. We don’t have time. And it just gives that focus. And it creates a route if you like in that huge data ocean, it gives us the focus from the very start. The clearer we are on the business question we want to answer, the quicker we’ll get to the solution.
Absolutely, there are really two things that really inspired the move. The first thing was, I really wanted to try and bridge the gap between business and data. And by that, I mean really putting data in the boardroom. And the reason for this was because over the years I’ve observed a lot of discontinuity between leadership teams, boardroom-type people, and analytics things that were doing analysis in the corner of the organization. And a lot of these analyses just weren’t being promoted enough and being used properly.
One of the key reasons for that was because of that discontinuity. And a lot of these analyses were just focusing on the things that really mattered to the people in the boardroom. So, one of my missions is really to bridge that gap and really making sure that the analysis that we do are completely business relevant. But also making sure that leadership teams are aware of, the art of the possible with data and how data can absolutely support them, day-to-day. And actually, going back to the topic of education, I also strongly feel that leaders, leadership teams need to be trained on data because there’s a lot of misconception around what data can do and it can help absolutely everyone in the organization.
What’s my biggest challenge? I think working with large organizations because you’ve got, many, many different teams sometimes. It’s really hard to understand how they connect with each other and how to make sure that they can shine, basically. And finding your way through because sometimes a lot of these organizations are very fragmented and we’re talking about teams that don’t necessarily talk with each other. Sometimes there is a bit of overlap in terms of what each team does and some potential internal competition. So, that’s always the difficult bit.
But I really feel that it is absolutely possible and I have seen it work bringing different teams together around a common data agenda by making these people part of the data game if you like. And once people realized that actually “Yes, I do have a role to play in this data agenda because I’m an expert at…” whatever, it could be marketing, it could be design. “I am an expert at this and therefore, no one knows this as much as I do. I just need a bit of a data lens”, if you like, “and I’ll be even more efficient.” So, it’s really about communicating data as a service, something that can really help teams, as opposed to, “You’ve got to do it. You have no choice, because, otherwise, you will be left behind.” Now, that can work in some instances but that’s not very sustainable and that’s not how you get long-term buy-in. So, I think focusing on the people first and then the data is probably how we will achieve a lot more.
Learn more about Penelope’s work at thedatatouch.com
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