Maximizing a Product Rollout with Incentive Management
Bringing a new product to market or even a new version of an existing product is not what it used to be. Back in the day your market was probably empty, a green field where you could find opportunity under a rock. Everybody needed what you had and selling was relatively easy.
But things don’t stay that way for long and today you have to work hard to insert a new product into a crowded market. As a result, a product launch takes on the proportions of a military campaign. You gather information and make projections, your marketing team develops and positions their ammo, and you train your sales troops and drill their objectives into their noggins. Then you go to war.
Ok, so the metaphor is deliberately hyped but there’s still a grain of truth in it. Rolling out a product is a big deal, it does require careful planning, and there are a lot of moving parts, which is why there’s so much planning to begin with. In short there is risk. However, there is always risk in marketing and sales. There is risk the market will change and your core product will get on a fast track to commodity status, a risk that your sales team won’t be able or inclined to sell it. A product rollout is just one more risk.
Most often we handle risk through a portfolio strategy, we don’t put all our eggs in one basket, as Mom used to tell us. We get that but how do we use this wisdom in a product rollout?
If you have more than one product, you already have a portfolio though you might ignore this fact. Each element in the portfolio has a risk associated with it and — get this — the risk is perceived differently for the business and the sales person. The sales manager and anyone higher up understands the importance of selling the new, new thing. It usually has the best margin and is more profitable than older items that are rolling down the road to commodity-town. Everyone should want to maximize the new product, right?
Well, if you are a sales rep, the risk you see is in the grind to make quota. If you are compensated on revenue and not profit, loss, or margin, then the fastest and easiest route to the cheese is often by selling what you know best because, hey, revenue is revenue. That’s where compensation management makes a great contribution. Using compensation management gives an organization and the sales team the chance to balance out their respective risks.
For the business, this means assembling a portfolio of requirements or expectations that include supporting the new product rollout as well as maintaining the continuing business. Many organizations will put a separate quota on the new product to ensure compliance so that while a rep might be able to make a lot of money avoiding the new product, he or she will not be considered a solid citizen without also contributing to the rollout.
For the sales rep, it’s all a game anyhow, in the best sense of the word. A mixed portfolio of quotas is just grist for the how-am-I-going-to-make-club-this-time calculation that everybody does.
So the sides are evenly matched, except in one very important area. How are you going to keep score? For sales reps, score keeping is done on a W2 form, but for managers it’s much more difficult. Let’s agree that we never want to hand out a goal and an incentive unless we have a way to measure attainment. The spreadsheets that many businesses use for relatively simple, how-much-did-you-sell incentive compensation calculations basically roll over and play dead if you have to begin figuring out multiple products, their unique incentives, and attainment — and we aren’t even bringing splits into the discussion.
Very quickly several things become increasingly clear. First, while you might have gotten away with using spreadsheets for incentive compensation in the good old days, today is different. Second, taking a portfolio approach to selling makes a lot of sense, if you have the tools to do it right. Third, you have to stay ahead of your competition and in this case it means if your reps are using spreadsheets to track their individual performance, it’s time for you to get more sophisticated by using a modern, database-backed system that can easily track multiple people, products, incentives and more. Only then can you accurately and fairly reward the people who took the greatest risks and met or exceeded expectations.
Woody Allen once quipped, “To a knife fight, always bring a gun.” This is like that.
The Incentive Compensation Process
The story of front office automation is shifting from data to process, but the idea is so new that you’d be hard pressed to identify a movement by that name. However, I am happy to coin a term and if you consider the developments of the last decade a clear picture emerges.
CRM and other front office solutions emerged as systems to manage data capture and retrieval. SFA managed the data collected about prospects, contacts, and deals; marketing managed aspects of lead development and marketing spend; and service systems juggled data about customer service needs. In all cases CRM systems served up data for human decision-makers to use in performing largely manual activities.
Then the Big Data revolution happened and its first effect was to document a need to simply handle all of the new data being churned up by social and other customer facing systems. But once data was corralled, data scientists began using analytics against the data to discover new information about business. This created a positive feedback loop in which growing databases provided information back to business practices and in the process improved them. Process automation soon followed.
Today big data and analytics have spawned the move from data management to process management throughout the front office. In some cases this movement has created whole new automated business processes and incentive compensation is a great example.
As a process, incentive compensation is not new, but its automation and the extent of its influence is. It had always been a time consuming manual process with limited applicability — business leaders may have known what to do but lacked the tools. At its greatest extension, the manual incentive compensation process applied to executives with employment contracts and to sales people with quotas. Human Resource departments handled executive incentive compensation while the finance group manually reconciled sales and commissions — a long and labor intensive effort.
As Chris Cabrera documents in his excellent book, Game the Plan — Every Sales Rep’s Dream, Every CFO’s Nightmare, automating the compensation process has spawned not only an automated incentive process, it has also introduced a new best practice.
In sales compensation it was always assumed that savvy sales people could game the compensation plan to their advantage. A wise saying in compensation management is that you get the results you incentivize and the caveat is that we sometimes inadvertently incentivize the wrong thing.
Gaming the plan is the inevitable result — in other words, without any formal process orientation by most companies, their sales people invented their own processes. Typically this means sales people preferentially peddling the products that are easiest to sell or that have the highest commissions or generally doing whatever is the easiest path to quota attainment and maximizing their commission plans. Too often though, reps’ ambitions do not square well with management’s needs, for example, to sell the new product which might be the future of the business but would require more sales effort.
That was typical in an era when compensation management meant capturing sales data in spreadsheets and manually checking for business rules compliance — accelerators, spiffs, contests and the like — and calculating compensation. However with automation of the core compensation process, companies have discovered they can move the discussion upstream from compensation after the fact to incentives before the fact.
With incentive process management vendors are now able to develop plans that more accurately reflect the goal attainment they intend paying commissions for. None of this incentive management precludes a sales person from attempting to game the new plan but it does change the rep’s calculations. By managing incentives better sales managers can set specific goals by product, revenue, and even profitability so that the path a sales person takes to quota is more inline with the company’s objectives.
Improving the incentive compensation process is also in line with other process advances now circulating. According to CSO Insights, and their twenty-year longitudinal study of the sales profession, the heart of sales attainment improvement is deploying better processes throughout the sales organization including in hiring, coaching, and managing sales teams. For instance, their studies have conclusively shown that businesses with formal sales processes, especially when backed up by automation (they call this dynamic sales processes) significantly outsell their competitors with random or informal sales processes.
In this light the incentive compensation management process is an important supporting business activity that feeds into overall sales improvement and there’s plenty of room for improvement. CSO Insights market study shows that only 57 percent of quota carrying sales people made or exceeded their targets last year. That means 43 percent failed to bring in the revenue that their companies were counting on.
It’s impossible to always get 100 percent of a goal but there’s plenty of room for improvement and incentive process management is a worthwhile investment for many companies trying to get to the next level of sales performance.
The Year Ahead
I’d like to say it’s going to be a good year in CRM and I firmly believe it, though I can’t offer a single all encompassing reason for my optimism though there are plenty of small things that begin to add up. In an earlier time the metaphor might have been “straws in the wind.” So what are they?
First, the economy is looking better but that’s faint praise. Things are not as bad as they were a few years ago, for instance the economy is adding in the neighborhood of 200,000 jobs monthly but I read an article the other day that said at this pace it will be another five years before we’re back to the employment level before the crash — in part because we need to absorb all the people who are entering the workforce. But as I like to say, black ink is better than red no matter how little there is.
More concretely, in our financialized economy, the markets are healthy and the broad CRM industry is doing its part to pump out new public companies. While all of them can’t be Salesforce caliber there have been many recent IPOs and the new year looks to have a few more teed up. That at least shows us that companies are evolving as they should and finding markets for their wares.
As usual, companies that are expanding the margin of our markets are the ones to keep an eye on. While I have seen my share of emerging CRM companies as an analyst and a judge in CRM Idol, the ones that are most interesting are those at the margins while the companies that try to reinvent the wheel don’t usually capture the imagination. Companies that I am watching for the year ahead include Xactly, InsideView, TreeHouse Interactive, Scout Analytics, Full Circle CRM, Lattice-Engines, HubSpot, Apttus, and Zuora. My good friend Paul Greenberg will publish a list of a bazillion companies he likes in his watch list. This is not intended to be all inclusive, just a smattering of companies I am well acquainted with.
All of these companies are expanding the margin of the market, expanding our horizons, and while only a few will have an IPO this year, the rest are worth keeping tabs on for sure. IPO candidates in my humble opinion include Xactly, Zuora, Apttus, and InsideView. Interestingly, none of these companies is what you would call a social company, which shows that there are more margins than just social. However, each is squarely positioned as a SaaS value proposition and that says the cloud is a live and well.
Xactly is reinventing compensation management, not just for sales where it got started but in every department of the enterprise. Zuora is making the subscription model mainstream by making accounting and finance in this new world easy. Apttus is a double or triple threat offering configuration, pricing, and quotation technology but they also have invented a way to be into and using Microsoft Office applications in conjunction with SaaS products like Salesforce. The result is a new kind of uber app. Lastly InsideView started as a sales intelligence tool but is expanding its footprint to provide sales and marketing teams with the data and insights they need to pursue opportunities.
I am warming up to TreeHouse because they have an interesting product line including partner relationship management (PRM) and marketing automation. PRM is one of those things that has come and gone more than once over the last twenty years, always with different players. I think this time might be significant as increasing numbers of vendors seek quality partner channels as a means of streamlining their operating costs.
If there’s a theme for the last group — Scout Analytics, Full Circle CRM, Lattice-Engines, HubSpot — I’d say it’s analytics. You might not think of HubSpot as an analytics company, and I don’t think they are one. But analytics is a part off what they do when they provide inbound marketing solutions. Inbound, done right, can be a big boon to business.
The other three offer mainstream analysis, if not analytics. Full Circle focuses on marketing management which I have written about many times because I think the idea of understanding the data and the metadata of marketing programs can do much to make you look smart if you’re a marketer. Lattice loves to crunch data about marketing and the sales process and they do it well. I don’t know any sales manager who doesn’t want better knowledge about all of the processes his or her team is involved in and Lattice is one way to get it.
Lastly, Scout has more mainstream analytics but for subscription companies and they make a good partner for Zuora. Subscriptions generate mountains of customer use data that can be used to predict everything dear to a subscription company’s balance sheet — I mean heart. With Scout’s analysis of use data, companies can spot revenue opportunities as well as danger signs like potential churn. Any way you slice it, this makes knowledge and that translates into market power.
So that’s some of what I am looking at as we start the year. I think it will be a year of base hits with an occasional sprinkling of home runs. Many, though not all, of the companies in this article have raised significant cash over the last year indicating both that the VC markets believe in their stories. But this also means clocks are ticking, investors want to see some returns and IPOs or private sales are on deck. Either way this makes for an entertaining start to the year.
Happy New Blog
Once a year I write a post that tries to predict some of the big happenings of the year ahead. The success of these efforts relies on clear thinking and objectivity — trying to figure out what will come to pass rather than what I want to see happen. It’s hard but thankfully no one ever checks up on me a year later.
First, let’s take a look at the general economic outlook. The global economy is improving, unemployment is trickling down at least in the U.S. and there are some bright spots like improvements in manufacturing and construction. The Federal Reserve is poised to get a new leader and Janet Yellen has been nominated though at this writing it is far from certain that she’ll pass the senate because she’s a Keynesian after all.
But in a recent Op-Ed in the New York Times, Martin Feldstein, a professor of economics at Harvard, who was chairman of the Council of Economic Advisers from 1982 to 1984, under President Ronald Reagan, suggested a very Keynesian stimulus so perhaps some further stimulation of the economy could be in the offing.
Long story short, the economy is looking better than it has for some time but it’s not great. On the other hand, there is a goodly amount of capital floating around looking for homes in late stage start-ups and the class of potential IPOs looks strong with names like InsideView, Xactly, Apttus, TOA Technology, ServiceMax, FinancialForce and many others. None of the CEO’s want to talk about that stuff, it’s like each is a pitcher in the dugout in the 8th inning of a perfect game.
All of these companies offer SaaS solutions and all are available on the AppExchange which suggests that my universe needs to expand. Nevertheless, the Exchange is a good place to look for signs of opportunity. I suspect application stores or exchanges are going to be very important incubators for new ideas in front office computing so I’ll continue watching them for new signs of life. You never know what you’ll find.
I expect a continuation of a trend that started last year in which marketing became the new darling of the front office suggesting that customer service (which is always important) is cycling out. Service is where vendors go during downturns so that they can try to protect existing revenue streams and, of course, SFA takes a back seat. But after a year of marketing hoopla I think the stage is set to put more wood behind the sales arrow to begin reeling in some of the leads that new marketing systems have been nurturing. So I am looking for new activity in the SFA part of CRM. But not just any activity.
I am still digesting the Bluewolf report “The State of Salesforce” that came out just before Dreamforce. One of the most intriguing findings from the report is that community is the new CRM. If that’s true, it is fairly easy to postulate significant changes to the way we sell. Perhaps sales people will become more involved with communities sponsored by their companies as a way to accelerate sales processes and lower the costs of making customer calls. What sales manager wouldn’t like that?
But I think the hidden message is that community will evolve more as a marketing and service hub, than as a sales tool. Sales will be a by-product of a lot of customer-to-customer interaction. Currently communities are mostly thought of as a part of marketing or as a part of service but I do not think it too far fetched to consider the possibility that community will become its own entity on a par with sales, service, and marketing — its primary consumers. Away from its departmental blinders, the community might be more able to take action to benefit all departments instead of just one.
Run well a community can provide a lot of information to a company and at some point it might make sense to give it its own charter and budget rather than having it mooch off the budgets of marketing or service. I suspect when that happens it will get a new name. Right now we have IT, which takes a technology perspective and that perspective is valuable. But this new entity will be more focused on information development or intelligence. This seems right and I like everything about it except the moniker. No one is going to want to work for ID, just a hunch but I can’t see calling the new department the intelligence department. Given the NSA’s reputation right now, we’ll keep clear of that.
This transition won’t happen over night so it won’t be complete in 2014, which sort of gets me off the hook in prognostication. But from another perspective, the oft quoted Gartner idea that the CMO will have a bigger technology budget than the CIO in a couple of years, I think, goes to the heart of what I am saying. But it won’t be the CMO’s budget, it will be the CIDO’s or whatever we decide to call him or her.
Old Possum’s Book of Practical Big Data
Ok, the title’s a cheap paraphrase of the T.S. Elliot book that inspired “Cats.” You have to start somewhere and that’s as good a place as any. But stay with me, this goes places. A big group of cats is called a clowder. What if we could access a clowder of big data?
Big Data has been taking up a big part of my conscious life lately what with all the analytics vendors out there and so many companies trying to figure it all out. There are at least three issues that converge when you discuss big data, two that we know and one that we don’t pay a lot of attention to just yet.
The two devils we know are physical storage and analytics and many people stop there. Storage has largely been taken care of with dirt-cheap spindles, the cloud, and other advances. Analytics is an old story that’s gotten better year in and year out. Huskier processors, bigger spindles, and in memory databases have made real time slicing and dicing easy. The other day I spoke with Alan Trefler, CEO of Pegasystems who told me that software and hardware have advanced in equal measure over the years to the point that today we can do quite a bit of analysis in very little time.
Batch pattern analysis gave us the input we needed to get predictive, to assign probabilities to situations based on prior experience and that has given us the ability to stack rank ideas, offers, and generally to be able to say this is the next best thing to do or offer — not always but — in this particular situation. It gives us the ability to (sort of) be in the moment with customers.
Predictive modeling has been a great way to enable companies to better understand customers and their needs. Based on company-gathered and maintained big data we can confidently deploy systems that suggest to employees what to do next. In case after case that I listened to in Orlando during Pega’s user meeting, Pegaworld, I heard of huge improvements in business process results, in part due to leveraging analytics and big data, so good for them.
But please pay attention! In these last few paragraphs we’ve traversed the long path from data to information. Did you catch it? Maybe not. Analytics turns data into information and people (usually) turn information into knowledge. Our systems serve up information but our people, our employees apply that information in customer facing situations to make decisions that achieve desired outcomes. There’s nothing more important that good decisions in business today which is why we are fixated on big data and analytics. But we can’t stop there.
It’s time to think bigger. What would it be like if we could amass more data than a single company typically captures for its analysis? Naturally, this assumes all the data is relevant to a set of business processes. It’s very hard to do something like this. Some vendors I’ve spoken with about this say that the data lives in many places and consolidating it is not necessarily quick or easy.
One place where it might be easier to accomplish this kind of Major Big Data consolidation — can we start calling it Major Knowledge? — might be in SaaS applications. Of course not just any software as a service but those systems that operate on multitenant storage might have an important leg up. A company like Salesforce, NetSuite, or Xactly might be a good place to look. In a recent conversation I had with Chris Cabrera, CEO of Xactly, I heard they were thinking about what that would look like.
You may recall that Xactly focuses on incentive compensation management. Xactly collects data that focuses on sales people, deals, credit (for partial deals), compensation, and much more. If properly scrubbed so that all identifying data is removed, this database would be capable of revealing all the best practices information in sales by examining the way that people are compensated, no small accomplishment. In the right hands, that information can become powerful knowledge. I know some of you are saying why not look at other data like revenue or stack ranking the reps or any of a thousand things.
The answer is simple. Other data won’t give you the answer. Incentive compensation is an art at the moment (unless you already use a system like Xactly) and relying on a single data set might only reinforce bad practice. Capturing data from a wide body of knowledgeable sources is, after all, one of the hallmarks of crowd sourcing.
People do their jobs and they get compensated and someone is the top rep and someone else is at the bottom. But these rankings don’t say anything about whether the incentive compensation was really an incentive, whether or not it caused people to modify behavior.
So what, you might add. But wouldn’t it be nice to know if the incentive is both effective and in the right proportion? What do others do? Effectively, what’s the best practice? Those are questions you can’t answer if all you’re looking at is your own data.
Sales comp is a big hairy issue. It’s estimated that in the United States alone companies spend $800 billion per year supporting sales based incentive compensation.
It’s messy and full of 25% credit for this deal and 65% credit for that; it also has accelerators and clawbacks so how do you get it right? For example, Xactly found that 75% of its customers are crediting five or less individuals on a deal, but some outliers credited up to 161 individuals on a single deal. Splitting a deal 161 ways can hardly be motivating. Many are the stories of sales people who left a job because they felt under appreciated (i.e. compensated) or just thought they could get a better deal elsewhere. Having access to information based on such a huge volume of data might give every sales manager and HR or- finance department the concrete information they need to do a job they are largely guessing at right now.
Sales compensation is not the only area worth exploring with this approach either. The same techniques can be applied to every job category and if you’ve looked lately you will have seen that many jobs are coming to have incentive compensation as a part of the package. In fact, an estimated 84% of companies today are now using some kind of incentive compensation outside the sales function. If you ask me, there’s never been a greater need for the kind of data resource pooling and analysis I am proposing here and it’s easily within our reach. We just have to think a bit different about the challenge at hand — how to attract and retain the best talent — because business today is less about your widgets and more about the quality of people you have representing them.
