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SPOTLIGHT: Customer Analytics Q&A with Accenture’s Julio Hernandez

Originally published July 11, 2011

BeyeNETWORK Spotlights focus on news, events and products in the business intelligence ecosystem that are poised to have a significant impact on the industry as a whole; on the enterprises that rely on business intelligence, analytics, performance management, data warehousing and/or data governance products to understand and act on the vital information that can be gleaned from their data; or on the providers of these mission-critical products.

Presented as a Q&A-style article, these interviews with leading voices in the industry including software vendors, end users and independent consultants are conducted by the BeyeNETWORK and present the behind-the-scene view that you won’t read in press releases.

This BeyeNETWORK spotlight features Ron Powell's interview with Julio Hernandez, Executive Partner and the Global Lead for Customer Analytics within Accenture Analytics. Ron and Julio talk about using data and analytics to engage with customers.

BeyeNetwork spotlights focus on news in the world of business intelligence, and I’d like to drill into the results of Accenture’s recently completed Customer Analytics Survey of 800 directors and senior managers at blue chip organizations.

Julio Hernandez: Thanks for allowing me the opportunity to chat with you.

I found the Customer Analytics survey to be very enlightening, and I really want to share this with our readers. Organizations throughout the world are now recognizing the benefits of using data and analytics to understand their customers, and this survey yielded, in my estimation, some very surprising results. But let’s start by having you tell us about Accenture’s customer analytics practice.

Julio Hernandez: Accenture Analytics is our group that basically shepherds analytics at Accenture. We are part of a global network of over 20,000 analytically skilled professionals. We have experts who help work on setting analytic strategy and enabling it by defining the infrastructure that’s required, the types of analytics that need to be done, the human performance management of actually trying to manage analytical folks, and we also have management scientists who create models and  the like. We also help our clients with identifying what their data strategy should be and help them determine if they should incorporate third-party data and so on. That's how Accenture Analytics is organized, and within that I actually run the customer domain, which is focused on the marketplace and customers so that we can help enterprises develop more relevant value propositions and also serve their customers in a much better way.

How do you define customer analytics Julio?

Julio Hernandez: We look customer analytics very much from a functional perspective – from four or five different areas. One is, first of all, around sales and marketing. The second is around service, the information you would need to be able to serve your customers. We also look at it from pricing and a new product development perspective. We think about those areas as being very germane to customer analytics. Then within that, there's the requirements, if you will, that you need to have to be able to do analytics, and part of that is the data infrastructure. That includes identifying things such as the technology, the customer data warehouses, that our clients would need. What is their sourcing strategy from a data perspective? The third is what are their methods in terms of basically being able to do different types of analytics from very rudimentary descriptive analytics – reporting and the like – to very much more predictive and high-level analytics around optimization, forecasting and propensity models. And then we also think about how to infuse those analytics into the channel. So when we talk about analytics, we think about it from end to end because, frankly, what we see is if companies don't actually think about that way, they may have very interesting insights but they don't apply them. That's how we view analytics at Accenture.

I agree – it's always closing the loop that I find the key. And so many times you get to a certain phase within a project and you never get to closing the loops. It sounds like you have that integrated into your strategy.

Julio Hernandez: That’s very true Ron, and I would tell you there are a couple of things that I think really help companies think through that and accomplish it a little better. First and foremost is actually going into it with the mind-set that we’re going to measure what we do. So if you put that closed-loop measurement in there, it forces you to start to really think about executing. And the second, and we have a large group of people that are dedicated to this, is that there is a human performance management piece here that is really required. As we talk about the survey, you’ll see some insights about leadership and how really critical it is to making sure that people don't view analytics as just a demand of the IT organization, but rather as the demand of the whole business.

Well, let's get to the survey. First of all, could you give us some background on the survey respondents and then also why you chose this area of research?

Julio Hernandez: First, we went out and interviewed about 800 senior managers and directors/professionals across the world. We focused on essentially eight major geographies: North America (the United States and Canada), the UK and Ireland, Germany, Italy, Spain, Brazil, China and Japan. We wanted to get an understanding of what was happening across the world. Secondly, in terms of who we talked to, we talked primarily to blue-chip organizations and we talked to directors or managers in those companies, the individuals who are really essentially responsible for enabling and doing something with this information. In terms of how long we were on the phone with them and the series of questions, it was about a 15-minute interview and we did this over the December/January time frame.

You know when I looked at the survey results, it seemed the good news from your research is that organizations are well aware that analytics has become mission critical in today's competitive marketplace, especially in analyzing and segmenting their customers. Can you tell us about the types of analytics organizations are using to target, service or interact with their customers?

Julio Hernandez: There are various types of analytics that companies are using. What I would tell you is that most of them have indexed around profitability for segmenting their customers, trying to understand who's profitable and who's not. We call it value segmentation. There are some companies that are segmenting them based on preferences around channels and where to engage customers. But, by far, the biggest one was really around value. Now how do they use that value? They use that value to define customer treatments – for instance, how they are supported in customer service. They use analytics in terms of some targeting of what they would try to sell to the customer. And then also, they would use analytics sometimes in terms of helping their sales organization. That was where the focus really was on the analytics. Now there were other areas. Some people are using analytics for pricing or for new product development, but those numbers were small. So the types of analytics ran the gamut, but primarily the focus was around value segmentation.

Value and profitability are so key today, especially with how competitive things are globally.

Julio Hernandez: Absolutely. One of the things that we often talk about is focusing on understanding who your best customers are and then also trying to understand how you might take the next tier of customers and make them more profitable. There was a strong focus on that, but what was interesting though – and what we saw as a bit of a gap – was that the organizations weren’t spending as much time thinking about what value the company was providing to the customer. In other words, as they started thinking about the customers, they didn't think as much about what the customers value, what the customers actually thought was of interest from the company. It was much more about what the company could do for somebody else as opposed to really understanding the needs of the customer. We feel you have to strike the right balance between value and also trying to understand your customer’s needs.

Well, with the wealth of information that companies can use to ensure that they’re meeting their customers’ needs, there should be a lot less unhappy customers or consumers out there. In reviewing the survey, I found it surprising that when making decisions about what customers want, many organizations are just as likely to rely on personal experience as on analysis of data and facts. Does that surprise you?

Julio Hernandez: No, it doesn’t. I think we need to think about this as an evolution and also think about this from a very human perspective – basically the way that people work. So I think first of all when we talk about intuition, many people’s intuition developed over time. They process a series of facts, and they categorize those facts in their minds based on their experiences. They realize they've seen something happen five times before so they go ahead and act on that. And, frankly, in the previous world, that might have been acceptable because the trends didn’t change as fast.

But now with the advent of social media, with the advent of people being able to interact across multiple channels, with the fragmentation of organizations and brands, all of a sudden you have much more information and many more touch points with your customers. Intuition doesn't necessarily represent the fast pace of change today. I think that's why we saw that result come across in the survey. But the second thing that I felt was most interesting was when we compared our survey to Accenture’s customer service survey that was completed in the fall. What we found is companies said they know a lot about their customers and, therefore, they should be able deliver a good customer experience. However, the customers were saying the companies were not delivering a good customer experience. So even with that knowledge, it has still not been translated into action.

Another surprise from the survey was the fact that most organizations indicated they were satisfied with the quality of their data. This is contrary to what we hear from some of the experts on the BeyeNETWORK. Why the contradiction?

Julio Hernandez: That’s a great question, and I have to call it a paradox. You have to “double-click” on that to really get underneath it. We found a couple of things. The first thing we found was the organizations who self-reported themselves to be highly analytical companies were the ones that said they were not satisfied with their data. On the other hand, it was the companies who actually said they were not that analytical who reported that their data is good. So what happens is if you actually play in the sandbox, you start to see that there are pebbles, and stones, and rocks in there that aren't the things that you thought they were going to be and that the data is not clean. Again, it was the people who weren’t spending as much time using that data who actually thought they had good data. The point is when you start using and relying on your data, you start to notice things that don’t make a lot of sense and oftentimes it falls back to the data. I think what's happening is that some of the survey respondents were not as analytically inclined as they think they are and they hadn’t spent as much time with the data.

And this is somewhat of a new area where the people within the business who are not statistical or analytic oriented are now getting exposed and working directly with analytics. It’s somewhat of a learning experience for the business, wouldn’t you say?

Julio Hernandez: Absolutely. Part of this is that it’s a learning experience, but I also think organizations and their leaders need to understand “the art of the possible.” They need to have proof points along the way that make them want them to go ahead and actually start relying on and using analytics more and more frequently. I mean the reality is it’s not that companies haven’t been using analytics. People have been using rudimentary analytics in terms of business intelligence and reporting and things like that. But when it comes to better targeting, better optimization models, better propensity models, these are things that they haven't been spending as much time with. And so I think, as you start moving up the hierarchy of the types of analytics that you can apply, you also have to demonstrate that making those investments and actually putting them into action drives value.

And if you do that, then you start to create a pull from the business and they start asking questions such as: Wouldn’t it be neat if we knew this? If we did this type of analytics could we figure out who we need to talk to? Where should we be making our marketing investment? What’s the best way for us to take our products to market? What channels are actually the most effective and most efficient and give us the biggest reach? So I think part of it is fundamentally starting to show proof points of value creation. Then the business will start to pull on it. Now the other tactic that we've seen is that, frankly, organizationally if you've got someone at the top of the organization who is demanding more facts, demanding more fact-based conversations, then that obviously helps people to push harder on the analytics as well.

Julio what do you see as the biggest customer analytics challenges for organizations today and are these challenges insurmountable?

Julio Hernandez: I think there are challenges but I don't believe they're insurmountable. And I think that the reward is there to justify spending the time, energy and effort on analytics. But I would tell you there are probably three challenges. We talked about one which is you have to make sure that you have the right data. Now that being said, you don’t have to wait to have all the data to move forward with analytics. Getting your data clean and putting it in a place where people know it’s available so they can access and use it is incredibly important.

I think the second issue is really around talent. The reality is that management scientists – the folks that do analytics, the statisticians – are becoming scarce and are very much in demand. That’s a very valuable skill profile. Having the talent in the organization and managing them the right way is another issue. And I'll be honest with you, I manage a lot of management scientists, and you have to give them a little bit rope to be able to do what they do best. But you also need to appreciate what they do because they have a unique skill set and look at the world in a very different way.

And then the third thing, which is not insurmountable, is an aspect of culture. Are you going to rely more and more on analytics and more and more on fact-based decision making, or are you going to rely on the legacy way that some of the decisions were made in the past based on intuition, experience, and conversations?

I think those three areas combined are the hurdles that need to be overcome. The rest of them essentially can be addressed with technology, with a little bit of investment and a with little stamina. But I think you’ve got to have the right data, you’ve got to have the right people who can do the analytics, and you’ve got to have leadership that wants and encourages the use of analytics to make better, fact-based decisions.

How could organizations today make better use of analytics?

Julio Hernandez: I think that’s a great question. I think you have to answer that based on the functional area. Then the second point is application of it. Where do you apply it? And if you get the intersection of those two points, you can add a lot of value. So for instance, we started this conversation earlier, Ron, talking a bit about the application of it, essentially making sure you close loop it. That's the first thing. You’ve got to make sure that you act on this stuff.

The second thing you have to understand is what are the core value levers that you would pull? So for instance, if you’re customer service person and you’re managing a customer service department, part of what you want to make sure is that you have the right engagement with your customers but that you do it at the right cost structure. So this would be of value conversation. It would also be a conversation around preferences and around effectiveness of each of the interactions. You would do analytics around that.

If you are a marketer, it would be very different. It would be: Am I pricing my product to the marketplace and to the customer based on their needs? Am I actually targeting them and giving them the right offer or the right value proposition based on the way that they use my products?

If you're new product development person, it would be: How are customers using my products? What are their unmet needs? How could they actually use my products in a different way?

So I think you have to answer that question much more from a functional perspective. But in my travels and my interactions with clients and in the marketplace, I can tell you that when we sit down and talk to these individuals – be it an automotive company, a telecom company, or an entertainment company – new product development wants better analytics, service wants better analytics, sales and marketing want better analytics. So I think there's absolutely a marketplace out there and a need for increased analytics.

When we talk to folks in the BeyeNETWORK and also SearchBusinessAnalytics, we see a tremendous amount of interest in analytics. I think this is really just the beginning of the next major wave in business.

Julio Hernandez: I agree. And, in fact, one of the things that we've been talking a lot about is if you think about the old way, 15 to 20 years ago, there was a huge focus on increasing process excellence and reengineering. Now we talk about essentially reengineering the way that decisions are made. It’s all about understanding how frequently you make specific decisions, who should be making them and what’s the information they need to have to make them so that these decisions can be made more effectively.

And secondly, I would say that one of things we’re seeing and what we're talking about a lot is essentially making sure that organizations have the right information because when they have the right information, they can then start to rely on their problem-solving skills to have a vigorous and a healthy debate about what the right strategy is and what the right tactics are as opposed to having a rigorous but unfulfilling debate about the value of the data or the cleanliness of the data or the findings. So we think this is absolutely the next trend, and it's going to be integrated into the way companies run their business.

I couldn't agree with you more. For the benefit of our audience, where can they access and download the survey results?

Julio Hernandez: They can access a PDF of survey results through our website. (Click here to access PDF.)

That’s great. Thank you Julio. We really appreciate the insight you provided for BeyeNETWORK readers.

  • Ron PowellRon Powell
    Ron is an independent analyst, consultant and editorial expert with extensive knowledge and experience in business intelligence, big data, analytics and data warehousing. Currently president of Powell Interactive Media, which specializes in consulting and podcast services, he is also Executive Producer of The World Transformed Fast Forward series. In 2004, Ron founded the BeyeNETWORK, which was acquired by Tech Target in 2010.  Prior to the founding of the BeyeNETWORK, Ron was cofounder, publisher and editorial director of DM Review (now Information Management). He maintains an expert channel and blog on the BeyeNETWORK and may be contacted by email at rpowell@powellinteractivemedia.com. 

    More articles and Ron's blog can be found in his BeyeNETWORK expert channel.

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