Interview

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Innovation leaders

MM: That’s completely fair. Lastly, I’d like to address the culture of change.

BK: Yes. That’s been the big frustration as a technology salesperson for 20-plus years. Technology should stay ahead of actual implementation, or I wouldn’t have anything to sell tomorrow. But being on the bleeding edge in most cases with these technologies, it’s been frustrating to find that getting folks to embrace change—not necessarily just technology—they expect, “I’m going to buy your stuff and I’m going to get all this great insight, and therefore, things are going to change.” Well, they’re never going to see improvements if the organization isn’t structured such that we’re going to take that information and make use of it.

MM: This gets to a real focus of ours around what I call, “Innovation Leadership.”

I’ve found that many product companies—whether Apple or HP or Bose or Ford… Many product companies have well documented, structured, and repeatable innovation processes for product innovation.

But when it comes to process innovation and service innovation, I’m finding that most companies are completely out to sea. Almost completely bereft of any structured or repeatable processes for innovating new processes.

As it relates to new technology, most senior-level executives—specifically those who are signing checks or releasing funds—tend to see their organization in terms of operational capabilities. They consist of systems, processes and accountabilities. I’d define an account-ability as an agreement by and between an employer and an employee. The account-ability is not just a role and responsibility but also explicit daily reporting requirements by which an employee reports on a daily and weekly basis some number of facts that—when rolled up—indicate an aggregate process toward strategic planning. Or progress toward objectives of the strategic plan.

But Bob, I’ve found that most companies have very fuzzy, indistinct if not conflicting accountabilities for people in their groups that work for them. As a function of not really having an explicit by and between an employer and an employee with a focus on not just, “Here’s what you do,” but, “Here are the five business facts that you agree to provide on a daily basis,” that will then roll up into some overall organizational performance scorecard.

As a function of indistinct, incomplete non-existent or conflicting account-abilities, it’s very difficult to introduce any proposed change into that organization. As soon as you say, “Well, let’s do this,” all of a sudden, you get a whole bunch of people in the room starting to turn funny colors and looking down at their shoes and saying, “But you don’t understand!”

Right?

BK: Absolutely.

Trusted Advisors of the Buying Funnel

MM: For me, I take this notion of a conversion funnel and call it a “buying funnel for new technology”. Most of the hindering forces to change really come back to fuzzy accountabilities. There isn’t anything that you as a vendor can do about the accountabilities, and therefore, the lack thereof in a buying organization other than to suffer RFIs. These are all endless sales cycles.

BK: Yes. I couldn’t disagree with anything you just said, because that’s the environment. I guess we’re starting to slip away from a technology discussion into a social behavioral discussion. I can only bring this back to my personal world.

MM: Right.

BK: I sell technology with a hope and an assumption that it’s going to improve processes and effectiveness, and make somebody’s life at the company I’m selling it to better. The personal account-ability and responsibility I want to take is constantly educating myself on trends, best practices and impact. And the result of that education and knowledge, I want to bring to the market by saying to my customers, “I’m not just selling you technology that I know has worked for others and I hope works for you,” because I can’t control you changing. Rather, “I would like to sell you technology as the first phase of a process of engagement that is continued consultation and mentoring on implementation and best practice.

MM: Yes. That really defines the role that I might refer to as a “trusted technology advisor.” That really emphasizes facilitating or enabling a new or enhanced operational capability of the firm. So getting people to choose what works almost always comes back to communication, interaction and collaboration that a trusted advisor would hold the context for. It’s about always having the next step clearly identified with some sort of 30- or 45-day plan that is moving you toward that particular step. Does that kind of describe your role, at this point?

BK: Absolutely. That’s a role I love to have. I think the challenge is always that vendors are looked upon as providers—not necessarily consultants or advisors.

MM: I think the vendor that succeeds in moving forward will, in fact, have to become a trusted technology advisor and an enabler of change— and a facilitator of the communication, interaction and collaboration that must occur across functional lines or lines of business within an organization, so as to unlock the value of the technology that they bought.

BK: Agreed.

MM: Fabulous. On that note, I’d like to conclude our session today. Thank you again.

BK: Absolutely, Michael. It’s been my pleasure.

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Integrated information for policy-managed decisions

MM: It seems that as your solution evolves to include WiFi Max networks and 3G phones—such as the iPhone—these mobile Internet connected devices become points of control of an entire industry, almost like the channel changer for a TV; it’s becoming the control system for these very sophisticated applications.

MB: I think of the world of mobile devices as a great way to give freedom to people who otherwise have to be slaves to the careful tending of systems and so forth. In that sense, they’re very freeing.

If you take the kinds of monitoring and management application that people want as a business intelligence solution and simply display it to them on a mobile device, you’re not going to be doing them any favors. You’re just changing the location at which they have to do a piece of work, where they look at a screen, make a business decision and so forth. It might give them some location freedom, but there’s a lot more potential out there for the activity you have to do, from the mobile perspective—to be a higher level of monitoring. You automate the decision-making at the lower level.

Today, let’s say you’re looking at a sales margin inventory kind of report. You say, “Gee. Here’s a product that I have very low inventory of, and I happen to be selling a lot of it. Gee. It’s selling at high margins. I guess I should reorder that.”

Of course, the system should just reorder that for you.

Today, people struggle just to get all that information on one line. So they can see that the problem is actually there. The next generation of systems will be ones directed at business rules that will help people automate the solutions. It’s what we call “operational business intelligence,” where triggers and tripwires and things of that sort can notice characteristics of the data in the enterprise, and can take actions.

Then from their favorite mobile device, people can make sure that the decision-making that’s happening for them is not going off the rails for some unforeseen reason. Instead of having to switch every switch on the train, you just have to see that the trains are all moving in a reasonable way.

I think the future will lead to integrated information properly displayed for human decision-making, to support of that human decision-making.

MM: And eventually, I guess, we get into policy-managed processes that basically report back to you that, “Hey. I did this. Is that okay?”

MB: Once you have integrated information, the sky is the limit with what you can do with it. Integrating the information and presenting it in a reasonable model for people has been the bottleneck and remains the bottleneck today.

MM: Well, that sounds like a great place to conclude. Thanks very much.

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IT Service Management as Model

MM: This mirrors what we’ve seen in the IT service management area. Specifically around self-managing autonomic computing, advanced by IBM and other vendors. The core building block concept of self-managing systems is something that they call the “MAPE” loop. That’s an acronym for Monitor Analyze Plan Execute.

If I can apply the MAPE loop to your conversion funnel, we need to do a better job of monitoring what’s going on in the conversion funnel.

The analyze part then really starts to ask—to your point—”Why are we only getting 3%? Why not 10%? Why not 20%?

This will go back and forth between the IT service management and the equivalent of a service level agreement. What set of ongoing benchmark scorecards can we establish with the idea that, “If we can measure it, we can improve it?”

Having really good performance indicators or performance benchmarks as part of that analysis becomes critical.

The other part then entails understanding what the data’s telling me. Back to the MAPE loop—the “P” of “planning.” Planning really entails having a framework by which you can execute. So it seems to me that once I’m monitoring customer experience and engagement success, now it shifts.

From, “Okay. Here’s what we need to do,” to, “Now, let’s do it.” That puts emphasis on engagement systems. Some of that maybe entails some sort of a dynamic messaging system. But it’s driven by some sort of analytic profiles or personas, and it has a bunch of content in the newsletter that was really optimized for the intended person, given their customer profile or session behavior.

That then suggests that as I start to react almost in second cycles, as they begin to receive these bounce-back or outreach confirmation e-mails, there are click URLs in the newsletter that if they click, basically validate, “Yes. We’re on-target.”

So there’s a closing of the loop between something that happened, some behavioral data generated, some analysis of that data in terms of, “Here’s what it likely means. Let’s go probe and test it—either as a function of something that was served on in the session, or something that was served by means of a messaging system subsequent to the session.” Closing that loop and then also validating that, “Yes, you are who you are, and you’re still interested in Category X or Y or whatever the criteria is,” that you’ve associated with a particular persona.

Then ultimately, we’re talking about maintaining that data in a useful way. Such that when you come back and visit again, there’s even a further tighter loop. Ultimately driving us all toward individualized content, where every page is my home page. Where all the search engines in a faceted search framework reflect the needs or the taxonomy of awareness, consideration, desire and satisfaction of, “me.”

Based not only on my transaction, but my brand interaction histories. That thereby closes the loop of what I’d call an overall engagement cycle.

I know that was a lot to listen to, but does that make sense?

BK: That makes sense. In my experience, the handicap to implementation or improvement is a culture of change. It’s an environment where you can be agile enough to ask those questions and then make the appropriate changes. That might be something as simple as, “Why is this page not optimizing correctly,” and then having an infrastructure where you don’t have to wait weeks or months for a web development team to make desired changes in order to have an impact.

I think the desired environment is something everybody would sign up for. Automating it or having technologies to support it would be a desire as well. Now it’s a matter of, “Can I get any bang for the buck if I spend moneys on systems?”

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The fact that your client is basically a browser means that you don’t have a bunch of fat clients to manage and synchronize and update and all that kind of stuff.

That basically allows you to bring a strategic capability to users at a highly disruptive cost. “Disruptive,” here being the classic definition of Clayton Christiansen in “Innovator’s Dilemma,” and seeing what’s next. He describes it as a “good enough solution at a significantly lower—if not almost free—cost.”

MB: Yes. What we’re doing is intended to eventually disrupt the typical development process of systems integrators building large-scale data warehousing systems and doing custom-designed data schemas and so forth.

Value-chain optimization

MM: In the spirit of value-chain optimization, the idea of giving tools—not just tools, but capabilities—to the people who understand the data and who can effect an operational or a tactical decision in real time as they run their business… can you provide a couple of forward-looking comments? Or what I call “future proofs,” in terms of how you see this rolling out or evolving over the next 2 or 3 years?

MB: Well, I can certainly tell you that the sophistication of these applications will be growing. I’d say over the last 10 years—certainly 6 or 7 years ago—there was a lot of talk about data mining systems, for example. But every data mining system I saw was a tool for an analyst to use.

I think this kind of advanced analytic technology is going to show up for the end users, and it’s going to be a feature of a product. It’s not going to be data mining. It’s going to show up in a way that’s meaningful to a business decision maker—as more data for them to look at and take action upon. It’s not going to be packaged as some sort of fancy data analysis tool.

I think that is certainly what our focus would be on—leveraging that kind of technology. Customers do want the capabilities that kind of technology can bring, but they don’t want it packaged for use just by data analysts.

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Hearing the Voice of Customers

MM: So as a way of starting to summarize these points—what are the things that a proactive eBusiness manager would want to do in terms of maximizing the efficiency of their nurturing process? Clearly we need to monitor what’s going on. Right?

BK: Yes. I think we need to monitor it at a very tactical level. Internet managers should spend more time answering the “why” questions that come from campaign reports, analytic reports, voice-of-the-customer responses, social media pages, etc.

“Why aren’t we getting the response that we expect on campaigns?

“Why are lengths of visits, page views, returns by recent visitors surprisingly up or down?

“Why is customer feedback so infrequent?”

MM: I’ve got data that says, “Oh. I’ve got a user experience or a user interface problem here; I’ve got fuzzy, indistinct content and product descriptions here; I’ve got an SLA that needs to be improved because I’ve got too many timeouts or I’ve got a server overload.” Something like that, right? So, in monitoring, you want to identify some number of things to do. Right?

BK: You’re right. In the beginning it’s about structural and technical issues that tend to be the “fires” that keep most organizations in perpetual reaction mode. Next the organization will focus on product, segment, campaign and other sub-groups to improve interaction and success.

At some point it should become important to transition from being reactive to being proactive. At some point in the life cycle companies will proactively focus on customer experience and improved satisfaction with an eye on turning customers into “raving fans.”

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Hidden costs

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MM: There was another dimension that you introduced. You kind of suggested a little bit in terms of needing to understand the behavior of a logistics supply chain—or in this case, a transportation value chain. In classic economics, according to the work of Ronald Coase in his book, “Theory of the Firm,” he would refer to these as “transaction costs.” Transaction costs was his way—as a theorist and economist—to describe all of the handoffs. The communication, interactions and handoffs—as well as the delays associated with getting a business process completed.

So you were really calling attention to the fact that there were all these other hidden costs—almost like opportunity costs. A percentage of the truck that wasn’t fully loaded, and the amount of time it was sitting some place.

MB: Or the inability to ship something at a certain time, for lack of availability of capacity, and so forth.

Solving many of those problems, honestly, is easy for people once you give them access to the information.

MM: Right. Because it’s their data.

MB: Yes. It’s their data. The big headache here is integrating it from multiple systems. Representing it in a uniform way for people, getting it in the form they need, and in front of the eyes of the people that have to take action on it.

In that sense, solving the transportation and logistics problem is not just a matter of some computer-science oriented thing. It’s just as much — or more — of the basics of data display and information integration.

That said, those practices have until now been far too costly and far too complex for many companies to acquire. So, that’s what we’re going after and trying to make far more cost-effective.

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Skill sets in predictive modeling

MM: As web analytics goes from more or less forensic reporting of anonymous behavior to now predictive models of what customers are likely to respond to, the underlying analytic discipline shifts from quantitative methods to things that are more forward-looking—be they game theory and predictive modeling.

When we talk about, “Who has skill sets in predictive modeling and econometrics?” Aside from analysts that are working at hedge funds and in New York City, and getting paid $300,000 to 500,000 a year, it seems to me that agencies will step forward into that opportunity with a founder or some equity participant. Secondly, it seems to me that there’d be a natural gravitation toward the largest concentration of PhDs in mathematics—India. And India may emerge, in fact, as the center of excellence for more prescriptive analytics and modeling of games, promotions and brand interaction through a lifecycle.

BK: I guess in response I’d say that the challenge the web analytics vendors play or have right now is that by and large, customers—people using web analytics tools—are implementing 20 to 25% of the capability of the solution to begin with. Limiting their use to data collection, analysis and reporting.

So, the more advanced, predictive modeling that you’re speaking to … while it might be something that they’ll ultimately build towards, the question is, “Will a majority of companies take on the task of implementing this capability?”

MM: I think that the agency will make that an opportunity and will invest in the tools and technologies to automate the tagging of your pages, and the reporting that comes from that, as well as the interpretation of what that means with very specific prescriptive outcomes in terms of what we need to build next.”

BK: I totally agree with you. I think it’s going to have to be a service provider. It’s not going to be the end company that’s going to try to have that expertise in-house.

MM: Yes.

Increasing Conversion Rates

BK: That argument could be fought from the other side, you should talk to SAS Institute where they have hundreds of Analytic PhD’s on staffs that are building very robust predictive models. The question is, “How many commercial companies are sophisticated enough to take advantage of that technology.”

In traditional modeling, companies continue to struggle with defining appropriate and action-able conversion funnels. Marketing is typically concerned with getting more visitors to the site and at the top of the funnel. And Marketing tends to be satisfied if somewhere between 2% and 4% of this top-of-funnel visitors make it all the way through since that meets with “industry standards.”

But who in the organization is focused on increasing that conversion percentage? It seems to me it would be more cost effective and more brand desirable to get a larger percentage rather than focusing on drawing more visitors in. Particularly in an environment of great noise, over lapping options, and fickle consumer behavior!

MM: Yes! The Miller and Heiman folks that came out with that canon of sales management strategic selling that came out in the ’80s—Miller recently wrote an article in Brand Week in which he describes the sales funnel. You call it the conversion funnel, which I guess is a little further down.

He said that most companies—especially younger companies—have these wicked peaks and valleys in their monthly revenue, as a function of spending too much time in the bottom third of the funnel—which he characterized as “closing.” In his model, he simply trisected it into prospecting, nurturing and then closing.

He said it’s very common for a company to spend most of its time-resource-money on the closing function – which leads to these wicked swings in revenue on a month-to-month basis. He said that ideally, you want to have an equal distribution of time, money and resources.

He was advocating—to contradict you a bit—to put more people into the funnel so that some number of them will bust the rate and zip right down to the transaction, because they’re so desperate to do something.

I think to your point Bob, most companies do a mediocre-at-best job of nurturing deals already in their pipeline.

BK: I would fully agree with you.

MM: I concur that for incremental investments, it would seem to me that if you could reduce your attrition rate by just 10%, you could in effect double a conversion rate.

BK: Yes.

MM: In terms of gain-for-pain, it seems to me that getting the easily implemented solutions done first would probably result in a very noticeable and tangible return on investment.

BK: Agreed.

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Nickels and dimes

MM: That was one of the things that really came through in your talk, Mike. First of all, you were approaching these applications that you call “diagonal applications,” really almost as a value chain optimization suite. So you’re looking not just at one business, but rather at how to optimize an entire value chain—irrespective of your location in that value chain.

MB:  I guess that’s a way to look at it. There is a collection of these Diagonal BI applications. We’ve tried to package a number of them in modules that can be sold to particular industries.

MM: There was another thing that was remarkable in your presentation. That was the ability for using all of these kinds of hidden charges in the trucking area. There were some terms that you used, but they referred to—basically—”hidden” markups.

MB: Yes. That actually brings me full circle to the point I started to make at the beginning of the interview here. That was about “tools versus solutions.”

When I said Oco is a provider of business intelligence solutions, well—every business intelligence provider will tell you they’re providing solutions. The question is “solutions for whom?”

If you’re a data analyst, then a data analyst tool is a solution to your problem. At Oco we’re trying to provide a solution to business users for a transportation cost minimization problem—as our example here. That application goes to the eyes of the business user—not to the eyes of a data analyst. It’s intended for use directly by the people that are in the trenches who need that information. That’s why I stress that it’s a solution.

MM: The nickels and dimes, to use a metaphor. Right?

MB: Yes. Well, because it really adds up. That’s the problem. This is part of the reason why summarized data cubes and so forth have given way to, customers saying, “I need to be able to drill down to the actual data.”

In a summarized data cube, you would just roll up all the accessorial charges noted above. If instead you can actually see what’s happening at the individual bills-of-lading of the trucks, you can spot many of the problems and identify the carriers charging more than others, and so forth—even though the line-haul charge which is the advertised cost of the shipping, is the same.

MM: I refer to these as “carbon monoxide expense items.” Carbon monoxide constitutes an odorless gas that you can’t see, touch or smell. But you know you have it because you have a headache. And if you’re in a cave, you know the canary dies.

MB: Yes. These are, in some sense, ways for people to slide charges in on you.

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Critical success factors of large-scale BPM projects

MM: Can you speak to some of the critical factors in terms of putting together an enterprise taskforce for a large BPM project?

IG: I think education is where it all begins. It’s going to be — as you said — a large project. You need to know what you’re doing. You need to understand the tools that you’re going to leverage. You need to select the right tool for the job. You cannot do that if you’re not educated enough about this space.

I think education and training is the absolute first step in doing that. Especially if you believe in the power of self-empowerment — if you want to be in charge of your own destiny.

That’s also an area where I believe these Samurais that we talked about before can play a very key role. You’re going to rely on them to be your coach and mentor throughout this journey. They’re going to help you. They’re going to transfer a lot of their knowledge. They’re going to facilitate the process in many ways.

So I would very strongly recommend that indeed you bring one or several of them, as opposed to taking the business problem that you have and giving it away to a system-integration partner that — again — will not allow you to learn anything about the way to solve business problems.

I think the second element is, you need to involve the different stakeholders. It sounds trivial, but I think many projects fail because they are not involving enough of the stakeholders that should be represented. I’m thinking the technical people and the business people. On the business side, you’ve got the process owner and the end users.

Many of the people — based on the context — should have a say about the problem to solve and the way you’re going to solve it. In many cases, that’s where it becomes much more difficult. Those stakeholders live outside of the organization. They’re partners. They’re customers. They’re consultants. Here, involving them in this project is a lot more difficult. That’s where using the tools that you mentioned that live in the cloud as opposed to being in your data center or on your laptop is going to be key. But I think the technical side of the story is only the easy part. Technology is easy. What’s difficult is people and culture. Organizations. Dealing with change. The fear of change.

It’s even more difficult when you do that throughout an extended value chain, where multiple parties need to be aligned. So, here my advice would be, “Don’t try to do too much too fast. Especially until you’ve learned some lessons about what’s working and what’s not.”

You might want to start with slightly smaller projects with lower-hanging fruits. Learn along the way. Get first successes under your belt. Then be a little bit more ambitious. Walk before you run. Right now, I think we’re at the crawling stage, to be honest.

MM: Ismael, I want to thank you again for the interview.

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Driving the R in CRM

MM: In my conversations with folks in Europe who really seem to be ahead of us, in terms of really understanding the “R” in CRM, really understand that first of all, you need to have a lifecycle model for what it means to be in a relationship with a brand. But also, do we have an explicit data collection model for collecting what I call “brand interaction data,” very early on in the awareness and consideration process?

Something else that I’ve seen in this area that’s really been a startling breakout success for some of the digital agencies is the use of viral videos that are part of a guerilla-marketing program. Viral videos explicitly designed for presentation and consumption at YouTube, FaceBook and some of these other video-sharing sites.

Then, tracking who actually downloads or posts or syndicates in those videos of their Blogs and writes about it. Then making an outreach to the people that posted favorable things about these humorous product placements. Almost like a paid feeding of viral videos.

BK: I’m sure it won’t surprise you to know that Coca-Cola spends a lot of time and energy monitoring that very thing. Feeding that very engine. You didn’t mention it, but I’m sure you’re aware of Second Life. Burger King in particular spends a great deal of time and money on Second Life, which doesn’t immediately correlate back to store sales, but certainly does speak to that lifetime brand.

How do we find our customers in their place of preference and continually reinforce the brand? There are certainly some forward-thinking companies that don’t necessarily interact and sell stuff on the web, but they’re certainly using those mediums to solidify that brand loyalty.

Game Theory and Coke Promotions

MM: I’m glad you mentioned Coca-Cola. They were one of the early adopters of this smart promotional platform from a company that’s since gone out of business. It’s part of ePrize, now.

It was an interactive, smart promotions platform. It had mathematics underneath it that came from two PhDs in mathematics and game theory. Preference options would be similar to when you get an e-mail from Amex or Delta Airlines and they say invite you to make a bid on these four packages.

They invite you to make a bid, combining n-number of airline frequent-flyer points, membership points as well as hard dollars. They will choose five people over all the contest participants who got those packages.

BK: Cool.

MM: The net result is they end up collecting a lot of data from you. After you do several of these preference options they know, for example, that you’re single and that you have a proclivity for fun in the sun.

There are probably three or four more meaningful things they’ve learned from you as a function of your preference options or preference bids. It goes to the underlying game theory of how you elicit truthful information from anonymous actors.

So, game theory is just the mathematics or science of incentives to induce a particular behavior.

Coca-Cola was one of the very first adopters of this very sophisticated gaming platform. The challenge of course of that otherwise elegant concept is that it takes real rocket science. It takes somebody who’s got a PhD in quantitative methods and game theory to really understand how to construct and design these interactive promotions such that it produces the desired result.

BK: Agreed.

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