Innovation In Practice | How MC Sonae Manages 100+ Tech Experiments Per Year

Bonjour, everyone, and hello, this is omnitalk Retail.

I'm Chris Walton.

And I'm Anne Mazinga.

And we are coming to you live from the Fusion Group's podcast studio at NRF's big show in Paris.

Oui, oui, Anne.

And we are pleased to kick off our coverage today with Rafael Perez, the head of tech experimentation at MC Sonet.

Rafael, welcome to omnitalk.

Thank you.

It's a pleasure to be here.

Thank you for the invite.

Well, Rafael, let's start by giving our audience a little bit of background on you and then on MC Sone, if you don't mind, just for those listeners who might be meeting.

Sure.

So I'm Rafael, quite passionate about startups, innovation, experimentation as a whole, and my role at MC Sanai.

It's all about experimentation.

So I lead the IT Labs team that runs the technological experimentation across the value chain of mc.

So we scout startups, we manage the experimentation funnel, we push them through the fence, through the funnel so we can explore that further.

About mc.

It's the leading retailer in Portugal.

We have food retail with different formats, supermarkets, supermarkets, convenience stores, online of course, as well.

But we also have health, wellness and beauty, cafeterias, pet care.

But let's keep it short, we have a lot of things going on.

And from a retail perspective, you really do run the range, right, from large size stores all the way down to small hypermarkets as well, right?

Yeah, we started with hypermarkets, but we felt that customers needed more convenience, more proximity.

So over the last 40 years, which is how old the company is, we've been evolving through the formats that our customers need.

So, okay, so going back to your job then, how do you decide what your framework is for which emerging technologies you should experiment and which ones are worth the hype?

That's always a big question.

Very scientific, I'm sure.

Yeah, it's a difficult one because it's not obvious, because you only know that's a hype when the hype is over.

Right.

So it's already too late.

But we've been trying different things from the past nine years that we created these experimentation team.

So we experimented.

Nine years.

Okay.

Yeah, it's been nine years since the creation of IT Labs.

We've been experimenting.

Really complex matrix where you look into, is it a tech push, is it business pull?

What's the potential impact, what's the effort, what resources do you need?

We measure that up or up to simple criteria like just effort, impact.

But in the end, to be honest, it's been Gut feeling.

It is.

Yeah.

But this gut feeling doesn't come out in a vacuum because it's connected with the market research we do, the customer behavior that we are following, our interaction with the business units.

But having all this in mind, in the end, it just gets filling.

But however, even if we bet on hype, that's fine, because in the end we learned, let's say, the metaverse.

It's something we explored for sure, but in the end we learned about it.

It's fine.

It was a lesson for us.

And fortunately, the company allows a culture where you can try experiment, and in the end, if it's not worth it, at least we know what it is, what it takes, and we move on.

So that's interesting approach.

So then can I assume then that you guys are pretty aggressive in terms of what you decide to cut back on to?

Like, do you take a close look at, okay, is it working?

Is it not?

And try to get out of it if you feel like it's not working very quickly.

Is that part of the process too?

Yeah, we have a very pragmatic approach.

So first of all, we start with a technical perspective.

Does it work?

Does the hypothesis that we are considering make sense?

If we reach to good results, then we move on to the next stage.

If it doesn't, we pick a different technology.

Our pipeline has more than 100 initiatives a year.

We push more than half to deeper exploration, and then we end up executing a third of it.

So there's a funnel that we push.

There are a lot of options.

So we, we follow what seems more promising.

Got it.

How do you then, Rafael, balance kind of some of these breakthrough technologies, like AI is one that comes to mind, you know, generative AI and search and all these components of AI right now that are really breakthrough technologies with some of those more incremental technologies that might take a little bit longer or require more experimentation.

How do you kind of balance that in everything that you oversee?

Yeah, another one that it's not linear.

Right?

But yeah, again, fortunately, the company has an organization, a structure that allows that to more or less happen naturally.

For example, within IT labs, we do a bit of both.

There are things that are breakthroughs that we have no idea even if it makes sense for retail.

The metaverse example I just mentioned, we were exploring it on the technology point of view and what angle can we see for.

For retail?

So we look into that, but we also look into technologies that adds up something to a current business that we already have.

We do that within the IT labs.

But we have other teams that also contribute to that.

So innovation, it's not just the responsibility of one team, it's a company wide responsibility.

So we have our delivery teams that engage on a regular basis with the business and they do new solutions as per the business request.

They improve the current solutions that we already have.

So that's another channel.

And we also have a dedicated innovation team that follows and supported by granted projects.

For example, they can push through those more breakthroughs that typically require more financial investment, more resources.

So we also use that as a tool to leverage more breakthroughs that typically requires more effort.

Got it, got it.

So the question of ROI always comes up in these discussions, you know, so, so how do you guys think about that as a discipline, so to speak, in what you're doing?

Where does it come in?

Does it come in at a certain process?

Does it come in early, does it come in later?

Does it come in at all?

How do you think about it?

Yeah, again, it depends.

A lot depends.

Right?

It's again a hard question because as I was saying before, within IT labs, we always look at things in two perspectives.

We start with a technology perspective first.

So we set a specific hypothesis for a specific technology and we run what we need to run to validate that technology.

If things go well, we already have a success for us.

So we already proved that that technology can take us somewhere, depending on what we are talking about, of course, and then we share the results, Then the business perspective comes in.

And on the business perspective, it's a little bit harder and many things can happen.

Sometimes it's a timing thing, so technology makes sense, but it's not the right time for us.

We have other priorities and if we do not have the commitments on the business side, it's not worth doing it right away.

So it holds for some time.

It can evolve to a broader pilot, for example, where we bring more data in, we generate more resources and we have better data to do a business case, for example, where we better analyze the potential at the potential roi.

Or in some cases we launch a procurement process because we try the technology.

The partner we tried might not be the best partner.

So we also might run that procurement process to see from that approach what other options we have so we do a better analysis.

So once again, it's definitely not linear.

It depends a lot on the complexity, the use case, the timing.

So net, net.

It's part of the process always.

It's just deciding when.

When is the right time to bring it into the discussion.

Yeah, definitely.

Otherwise, unless I've heard that ever explained.

Actually the business will be losing time and our partners will be losing time.

Something I value a lot.

It's a startup time because their currency.

It's time because they have a limited.

Right.

When you're working with startups, 100% they.

Have a limited number of PoCs they can do with companies.

So I also take that in consideration.

If I know that it's not going to be moving forward in the short term, I'm the first one telling them just hold, prioritize other retailers and then we speak afterwards.

My background with startups provides me that position of knowing how to be in the startup shoes so we can have a better balance and a good win win conversation among us and other partners.

That's a big nugget.

Well Rafael, I'm curious because you are evaluating so many technologies, what are you most excited about experimenting with right now?

Or what do you feel like you have prioritized on your team at the moment?

Yeah.

I believe the expected answer is of course the implementation of AI across the value chain.

Right.

But I'll try to move away from that obvious answer.

Good.

Because we would have said what specifically too.

Yeah, I'm trying to move away from that.

So we are actually running a pilot right now of in store analytics.

It's a technology, the use case, it's not new.

It's being able to have in store analytics just like you have for any commerce website.

Sure.

Number of visitors, the journey, heatmaps, all of that.

So how can we get that?

So as I was saying, use case, it's not new, but the approach is, it's a really light approach, securing data and privacy from customers.

Oh wow.

We just deployed it in one of our stores.

We are now running them, letting it run so we can analyze the data and the possibilities of what we can do with that data.

It's tremendous on layouts, on marketing, on hyper personalization and everything.

So it's something that really excites me about if the technology works.

So we are still on the technology side, testing.

So what kinds of things are you tracking then?

We are well going deeper on the technology.

We are tracking the sensors of the phone, even if the phone is on flight mode because the sensors are always emitting.

So we have some hardware on the store that captures that, that pinpoints that and can track any device that gets in store.

Then we map the areas, we cross the location and then we generate the.

Insights, try to get the X, Y and Z's.

Yeah, right.

Exactly.

Exactly.

Then if you move even to A step further, you can even include an opt in option on your loyalty card app.

And if you do that, you can do hyper personalization because you can target exactly where the customer is at the store when he enters.

You can trigger something to incentivize a loyalty based purchase or even push for retail media on specific aisles, specific products, specific promotions.

So that's, that's, that's the potential.

Got it, got it.

Do you guys have scan and go in your operations too?

And that, that could potentially be a part of this too.

Very interesting.

Yeah, we've always, we've always hypothesized about the day when we can analyze a store like an E commerce browser.

We haven't seen it yet done, but it's, it's getting closer and closer every year.

All right, we'll get you out of here on this.

Now you can take this question as broadly or as specifically as you want.

It's up to you.

But my question for you is which technology do you think is going to have the biggest impact on retail over the next 10 years?

Again, AI, right comes to mind.

Yeah, definitely AI.

But in particular with the evolution of AI and the integration of AI with autonomous robots, I believe it's where the potential might be given the time frame you are giving.

Okay, okay.

I'm going to call it.

Digital AI can already do so much more for retail.

But retail is still a very physical business.

We need to take products from one place to the, to the other.

Let it be to a store, from a warehouse to a store, from a store to a customer house, it doesn't matter.

And with the evolution of autonomous robots and the integration of AI, the smarter AI that we are seeing on those autonomous robots, I believe that within a 10 year time frame there's a lot of potential.

There's a huge incremental benefit on the instrument.

And you think that's in store, warehousing both sides?

I would say pretty much everywhere.

You can automate easily, warehouses, replenishment in store.

Because you start getting autonomous robots with the sensibility of a human.

Because one thing is a robot that just pushes a box from point A to point B.

But a robot that can pick up a specific product and even a fragile product and place it on a shelf, it's a completely different thing and completely different potential.

Yeah, especially with labor being such an issue cost wise and with the availability of labor in a lot of places.

Well, you heard it here first.

This man's on the front lines of technology innovation in Portugal particularly and across Europe.

They're very well regarded retailer.

Rafael, thank you for joining us.

My pleasure.

Thank you to Vusion Group for sponsoring our coverage here from NRF's big show in Europe in Paris.

And Anne, until next time, be careful out there.