Managing Emerging and Evolving Client Expectations
As clients make the transition to be more data-intensive, experience-based enterprises, there’s a technology component to that change, but there’s also massive organizational and cultural transformation required. The consulting profession is going to have to adjust.
In the spring, Consulting magazine brought together some of the best minds in the consulting profession in New York for an Executive Roundtable to discuss what’s next. Not surprisingly, most of the discussion focused on Big Data, analytics and new technologies that are shaping—and will continue to radically shape—the consulting landscape, particularly when it comes to managing emerging and evolving client expectations.
Peter Brady | Senior Partner, Consulting, McGladrey
Roger Carlile | Executive Vice President & Chief Financial Officer, FTI Consulting
Steve Deedy | Chief Administrative Officer, AlixPartners
Paul Papas | Global Leader, IBM Interactive Experience, Global Business Services
Paul Rubenstein | Vice President, Talent & Organization, Aon Hewitt
Craig Sanders | President of Enfathom, the business intelligence and analytics solutions division of North Highland
Lee Spirer | Executive Vice President, Global Business Leader, Navigant Consulting
Joe Tarantino | President and CEO, Protiviti
CONSULTING: It’s so rare to get all of you in the same room to discuss the issues of the day. I think Big Data and analytics will certainly be one of the biggest drivers of the future of consulting as far as serving clients. Let’s start here: What do you think data and analytics will do to the marketplace and what do you think it’ll mean to the future
Paul Rubenstein: At Aon Hewitt, we are managing data and providing services, and there’s a client expectation that we’re doing both. You can find intrinsic value and insight in that data that’s part of your consulting service that’s beyond what the client is asking you to do in any specific moment. That’s a huge responsibility that doesn’t necessarily have a cost structure or work flow attached to do it. It’s not easy; Big Data is hard to do. Some of these new whiz-bang technologies make it look so easy but it’s not. Just because you have the data doesn’t mean you can make sense of it and use it in a meaningful way for clients.
Paul Papas: I would agree with that. If you look at Big Data as part of a seismic shift, and when you look at it along with social, mobile, analytics and cloud, they are all shifting the way we do business. And the change will be rapid, for sure. Think about the smart phone: It was only launched about seven years ago. That’s it. The whole app ecosystem didn’t even exist seven years ago, Big Data and analytics didn’t exist seven years ago. This is transforming every client in every industry and they are all wrestling with this notion of how do you
do business in this new world that’s literally only been around for a few years.
Rubenstein: And we’re talking about clients that used to wait five to seven years for their SAP supply chain implementation to compete before they got data out and now they expect data and fancy graphs in no time. It’s an incredibly rapid pace of change.
Craig Sanders: And I think all of us around this table were done a disservice by the past two decades of transactional systems implementations. Our clients’ expectations are that we do requirements, then we design, then we build, and then we deploy. One of the reasons Big Data is so hard is because our clients expect us to come up with a hypothesis and then solve that hypothesis and it’s just not linear anymore. The fact-based culture that our clients are trying to pervade is in every practice. I work in data, so that’s fine with me, but our change management practice is being pushed to have more data-based work. This is huge, but our executive sponsorship comes out of a different time and place so many times they just don’t get it.
Rubenstein: And the data project never ends. It’s an ecosystem; it’s an upper spiral of knowledge and you’re never done. That’s really hard for people. And, one of the most difficult aspects of this is that it challenges the traditional notion of the Statement of Work (SOW) on projects. The one that we’ve lived with for years.
Peter Brady: I think we have to define what we mean by Big Data. Maybe because my focus is more on the middle market, but we see plenty of companies that say ‘let’s get everybody their dashboard and let’s allow them to play with their data’ and that’s not necessarily very productive at all. I don’t want to be a naysayer here, but I do think you have to apply a little bit of common sense and ask what’s really new about Big Data and what do we want to do with it?
CONSULTING: That’s one of the big questions isn’t it? What are we going to do with it?
Steve Deedy: I think Big Data and analytics has fundamentally changed the landscape here. We used to build something and then tell clients to ‘have a nice life’ and move on. I think this is different in many ways, but one big way is the price points aren’t the same. The deliverable is—and I don’t want to call it trivial—but it’s not that hard. We don’t get paid all that much for cleaning the data and presenting the data. But if you can get to the ‘so what?’ in the data that makes all the difference. That’s where the consulting piece comes in. We have the red dress. And the trick is to get the red dress to the store window before your competitor.
Rubenstein: When we entered this space, I actually looked at the model of the actuarial side of the business—think about it, complicated math, sets of numbers, interventions that you make will have incredible repercussions. What does an actuary actually do? He or she is a Big Data aggregator that pulls it all together for you. Now that you have the data, what are your sets of decisions? What does it mean? What are the possible interventions? Those models of consulting become a lot less project based and it’s shifting to how do we move to a new revenue model where we are advising you? And let me tell you, that’s a really high bar because clients are so much smarter than they used to be.
Brady: Let me give you an example of that. If you were to look around the world right now, how many people are looking at a procurement system for our firm? It’s in the hundreds. And if you were to wait another minute, it would become another hundred. Why aren’t we instantaneously, as consultants, sharing what we’re finding and benchmarking in real time what’s going on in that particular area across the world? We can do that in the cloud and use that to the benefit of our clients. Do they really want all that analysis after the fact? Why not benchmark what’s going on right now in real time?
Sanders: It’s old world vs. new world. Instantaneous benchmarking might be available and accessible, but are old world executives going to be comfortable with it? They’re not going to want to make business decisions on imperfect data. That may be where we are going, but it’s up to the clients
to ultimately determine when we get there.
CONSULTING: That’s a good point. How are clients feeling about all this data? They obviously want it, but would you say it’s all a little overwhelming for them?
Joe Tarantino: I think they want the data, they have the data and they are trying to figure out how to use it for some sort of competitive advantage, especially when it comes to trying to build customer loyalty. Look at the retail industry, or the financial services industry, they have all sorts of data around the demographics of their customers, what they buy and what they use. That data can be very valuable when building customer advantage. We’re spending a lot of time on the security side, and it’s bringing a new dimension to our business around protecting the data companies have on hand. We’ve seen this already with a few companies—Target or Neiman Marcus—where it’s a huge security issue for them. And breaching that security is a big hit to their reputation. We’ve been heavily focused on that.
Rubenstein: I want to thank you for that because you see these silos of data still existing even within their separate data warehouses. The consulting value of connecting seemingly unrelated things is where I think a lot of our value as consultants will come from in the future.
Papas: As far as clients and what they’re thinking about all this, I just want to share two data points. IBM hosted a CIO leadership exchange recently and we had about 150 CIOs from North America. The first thing that they all said was this is a huge imperative for them, they’re pouring a ton of resources and money into this, but then none of them really thought they were doing nearly enough in the area, which I think is interesting. So, that’s one data point. The other data point is around Chief Marketing Officers and a study we do every two years. We interviewed 524 CMOs. Interestingly, two years ago we asked about Big Data and 71 percent said they were under prepared to deal with it. So, fast forward to this latest study, and think of the explosion we’ve had in this area over the last two years. Now that same question’s response is at 82 percent. The rate of change is outpacing the rate of their efforts.
CONSULTING: What are clients looking for from consultants? Clarity? Predictive data? A few of you have touched on this, but are they comfortable making strategic business decisions based on data?
Roger Carlile: Analytics without understanding is dangerous and perhaps useless. I think clients want and believe that something that can be counted is more accurate than something that can only be felt intuitively. Consultants will do a lot of work to generate that need, but I’m not sure that the answers will be any better. This will certainly be good for consultants because you’re going to have to tune those analytics repeatedly. That’s particularly true if you’re going to talk about consumer behavior. And it’s good for businesses like ours because there are going to be a lot more problems, a lot more breakdowns and a lot more failures.
Brady: But if you take that to the extreme, look at the financial services collapse. I mean you can’t get much more data and you can’t get more predictive than what those guys had. Yet, look what happened.
Carlile: That’s just it… So, I guess I’d say to you all: Sell all you can.
Rubenstein: Predictive analytics does not give you a coin sort towards the best decision. It’s about being informed by the data not being a slave to it. That’s where the maturity of the end use comes into play. That’s why I say it’s so hard to do. It takes a unique skill set.
Carlile: So when you’re developing the skills and coming out of the school, data science is big right now. Suddenly, everyone wants to be an actuary. Suddenly, data is cool.
Papas: As far as skills, we need the quantitative resources, the advanced mathematicians to take consulting to the next level. But this flows through all of our traditional consulting skills. How do we build those skills? We’re working with one of our marketing clients in Australia and we’re helping them build a curriculum.
Brady: Earlier, you asked where the new frontier is and I don’t necessarily think it’s in Big Data, per se. But rather, I do think it’s in the predictiveness and the ability to coalesce expert insights around data and then build a model from that that’s accurate, not necessarily precise. I think that’s the way of the future. Otherwise, consultants are out of business.
Papas: Right. We would refer to that as cognitive computing.
Sanders: If you think about the handshake we have with our clients what it comes down to is correlation vs. causality. My stats person uses this one all the time: Shark bites are correlated to ice cream sales. Why? Because more ice cream is sold in the summer at beaches and that’s when and where most people are bitten by sharks. It’s correlated but it’s not causal. Where this gets really dicey for us is when our clients are looking for causality but what we can provide them is correlation.
Brady: Even if we stop selling ice cream, people will still be bitten by sharks. But what they want to know is how do we get people to not be bitten by sharks. If you had enough smart people, you could figure out where to go—in real time—where there were no sharks at all.
Lee Spirer: Our obligation is not to be satisfied with correlation. Our best clients want us to prove causality, and I think big data is accelerating a lot of trends that we see on clients demanding more value, different value relationships, more embedded relationships where you define your expertise. If you don’t have the expertise and you really can’t put the context and you can’t speak to causality, then you are failing your client. They will expect you to teach them how to do it, go home, and then be there on call for them. This is not a traditional consulting model.
CONSULTING: Is the causality inherent in the data itself? Do you need your own subject matter experts? Can you lean on the client for that? How do you see that aspect unfolding?
Spirer: We feel like we need the expertise. You need the cardiac surgeon and the data analysts sitting side by side to really deliver what the client needs, in my opinion.
Brady: But the key is not just one expert. What you really need is a cognitive system that embodies the very best expertise available and apply that to a model. That’s only a model and it doesn’t give you causality. But the system could learn as it goes.
Papas: This is what we’re doing with Watson, our cognitive system, which actually won on Jeopardy! a little while back. The point that Lee made about having both the cardiac surgeon and the analyst sitting side by side is exactly what we’re doing with Watson. Right now, we have Watson at Memorial Sloan Kettering and the Cleveland Clinic, and we like to say it’s getting its medical degree. It’s going through the process of learning. It’s digesting all the medical information that’s out there: Every clinical trial that’s ever been done, every piece of medical information that’s ever been published, all the medical journals, electronic medical records, case studies and medical mistakes that have been made.
All of it. As it’s drawing its conclusions on specific cases, it’ll tell you that it’s basing its answer on this set of data and it will also provide a confidence level on its response. It doesn’t displace the human who still ultimately has to decide a course of action but it’s bringing together all the available data with human expertise. So, we’re now at a point where physicians can have instant access to just about every medical fact that’s ever been known anywhere in the world in real time.
Rubenstein: It’s data from the machine upwards and it’s questions from human downward… and the meeting in the middle produces a conclusion. That’s the ultimate goal and it’s incredibly powerful.
CONSULTING: That is powerful. So, is this the future of the consulting profession?
Brady: The successful consultant of the future will be able to pull together all of that information and that expertise in quasi real time to solve problems to varying degrees of truth. It probably won’t be on the same level as Watson, but it will be very important.
Rubenstein: What we’re describing here is not traditional consulting, so it raises, I think, a lot of interesting questions. Like, how do we get paid for that? What does the SOW look like?
Papas: I think these are great questions and it’s a great point. There’s a commercial model that’s evolving here. How do we evolve in this new world? But I think there’s this bigger shift that’s going on—the nature of the work that’s required by our clients has become more multi-disciplinary. At least for us, we no longer see strategy separate from data or separate from design. They have all become linked. So, when we’re doing a project now for clients we’re always asking what type of project it is and often we discover it’s a bunch of things combined together. That’s where the consulting profession is going: The fusion of those three things. The firms with the ability to bring strategy, analytics and design together will be the ultimate winners, I think.
Sanders: There’s another shift that happening here. Our clients have drank the Kool-Aid that you have to compete on the analytics. We have a long history of helping clients figure out problems with data, but now they want to bring that in-house because that’s strategic now. Before it was just a question that I needed an answer to. Now it’s strategic. They don’t want the answer coming from an outside party, they want it coming from within. These teams that we’re bringing together are made up of the cardiologist, the chief medical officer, statisticians and others.
Brady: Because the data is a commodity and the real value is in the expertise.
Sanders: It’s pushing us upward in the organization, which is really good, but it’s challenging.
Rubentstein: With our clients, the problem is always defined by what consultant was let in first. If the leadership consultant was let in first, it’s a leadership problem. If the engagement consultant was let in first, it’s an engagement problem. And our clients still buy that way because they haven’t connected the dots.
Spirer: I actually think clients buy differently. It’s a quality of service or cost of service problem, and I don’t think they necessarily care who they bought the engagement from, it’s just a healthcare problem to them. Ultimately, it’s about assembling the right team and solving the problem.
CONSULTING: Does all this data and real-time feedback that’s available to clients now ultimately diminish the role of consultants? Are you still valued as a trusted advisor?
Brady: To the extent that we bring expertise to solve problems, yes. But as an implementor or as infrastructure, I’d say no. Every company has some aspect of data and that’s a commodity. So, it goes right back to the level of expertise that we can provide.
Deedy: I think it depends on who the client is. If it’s an IT client that needs to go through a bunch of data and make sense out of a mess and make it accessible and create a series of data warehouses, than yes. There’s an IT aspect of this and they will hire you to bring that level of service to them. However, the client that can be that game changer is the one that’s got those very specific questions that can lead to very specific results. The client with those questions are great consulting clients because they just want information and if a consulting firm can provide them the right answers to very specific questions, and that leads to costs going down, for example, or inventory going up, or sales increasing or a new market opening up, that’s very powerful.
Papas: I think it’s leading to a renaissance for our entire profession, and it’s a welcome change. Consulting was founded on the notion of bringing depth of expertise. That’s at the heart of what we do. So, if anything, Big Data, analytics, cloud, mobile, social are all forcing us to be the experts our clients need us to be. It’s also forcing us to deliver value. Clients need to see value being delivered. They need to see measurable results and outcomes. That’s also at the heart of what our profession does. So, if anything, all these forces are making us raise our game to fulfill our core mission.
Rubenstein: I would also argue that it puts pressure on some of our traditional businesses. There’s still money to be made in systems implementation but I see a shift. Clients used to buy on price or reputation of the firm, but now they expect us to have a point of view on how this implementation will be a means to an end. That’s a pretty high bar. And the client doesn’t always understand what end they’re looking for.
Carlile: How many CEOs and CFOs are justifying their spend on Big data with the assumption that they are getting rid of their spend on consultants? I think it’s a lot, actually. A lot of them are assuming that if they get their own people, who know the business a lot better than consultants do, the information they need, then they don’t need consultants any more. If your view of the world was we add value because we have access to information that our clients and other consulting firms don’t have access to, that’s gone. Your clients have that information or could get it really easily. So, it has to move to something else. I believe consultants are hired to make sense of a world that the client couldn’t make sense of. But if you can’t figure out how to get to the higher end of that information, you will go away. And the consulting business will go away, I promise you.
CONSULTING: So, what does that mean? Any other predictions?
Carlile: I’ll tell you one thing I think that will change: I think you’re going to see a rise of the in-house consulting firm. I think companies will give it a go internally fueled by their own data.
Sanders: I don’t see it necessarily as a cost play but more of a strategic one. I think companies want to own the decisions that will result in them being able to compete more effectively in the marketplace. We all need an R&D function that’s different than a competency model. If we’re going to be ahead of the Big Data game, we have to walk into the client with it already. I call it a show me sale. Clients want us to take a little cut of the data and show them what’s going to happen. It’s a totally new approach.
Papas: So this point that Craig made on Show Me, The Missouri Model of Consulting. When we walk into a client, it’s no longer an eight- to 12-week engagement and at the end we’re going to give you a PowerPoint deck and a series of recommendations. It’s show me this in real time, so that project has to be based on real analytics. All of our work is now starting with something we’re calling “Proofs of Value.”
Tarantino: It’s not necessarily just a competency around technology or data, but you really have to bring some industry acumen or something that brings value or insight to the business to add multi-disciplinary depths.
Deedy: And different companies are going to be on different points on that spectrum. Consulting wasn’t built on going into GE and telling them how to manage. The art of consulting is how you go in and deal with a company that can’t afford or can’t find or can’t retain the talent they need. The consulting play is we can provide an expert, they’re going to visit with you and make a big impact and then we’re going to move on. That’s a lot different than we’re going to pitch a tent, stay here, and we’re all going to have grandkids together.