17. Commercial Analytics Culture and Relationships at Merck
Thomas H. Davenport
The Commercial Analytics and Decision Sciences group at Merck is responsible for assisting with advanced analytics for all of the U.S. primary care, hospital/specialty, and vaccine products at Merck. Its focus is sales and marketing analytics, including customer targeting, segmentation, sales force sizing, promotion response modeling, ROI assessments, and other related analyses. The group’s primary mission is to help senior leaders at Merck make better business decisions about multimillion-dollar promotional and sales budgets. It has existed at Merck for over 15 years.
The group consists of over 25 full-time staff and several other external consultants. The leader of the group has a PhD in Applied Research and Evaluation, and most staff members have advanced degrees in quantitative fields, including operations research, statistics, and economics. Most of the group’s staff came to Merck from analytical roles in other companies spanning numerous industries, including consulting, large pharmaceutical firms, health services research, physician licensure, insurance, and consumer packaged goods. In addition, the group maintains close partnerships with a variety of external providers of data and analytical software and services.
The Commercial Analytics group has been involved in a variety of key decisions at Merck over the last several years. When Merck re-engineered its commercial model for U.S. sales, the group piloted the model before it was adopted with test and control groups. Other work has quantified the impact and profitability of virtually all major investments in the physician and consumer channels. The group has also created tools for optimizing sales force sizes and structures along with multichannel programs.
Decision-Maker Partnerships
The Commercial Analytics group maintains a close set of relationships with internal business decision-makers. They have very positive comments about the group’s role. One executive, responsible for strategy execution, commented:
A lot of times Commercial Analytics team members were my “thought partners” in implementing the new field organization. Working with them was a good way of thinking something through. We used them as sounding boards. They are very solid problem solvers and play the role of an objective third party.
The same executive said that the Commercial Analytics team was more useful than an external resource that did similar types of work:
Most of the other firms who did these new commercial models used an external consulting firm. We used them for some tasks, but we had our own algorithms developed by Commercial Analytics. They also found ways to optimize and test the pilots. It gave us a better result, as well as more internal buy-in.
The leader of a new business area that worked with Commercial Analytics also had positive comments about the value of the group’s work and their credibility:
Our business area is a pilot program. We want to show that it drives new revenue and provides better customer support. Commercial Analytics is measuring the impact of the pilot program. They set up a rigorous test-and-control approach... Commercial Analytics is very familiar with the business. They ask what business questions you are trying to answer, and then they identify how to measure them. They will analyze the data to see if they can answer the questions. Their level of objectivity is what you need to have; we need an independent source... At times in the past, Commercial Analytics had to tell senior management that their project doesn’t have good ROI. They are very credible when they do that. And if they say it works, there won’t be any doubt about it.
A senior executive at Merck with global responsibilities emphasized the value of having Commercial Analytics involved in the entire decision process:
They should always be at the table when we are making an important decision. I remember when we were evaluating the returns on a major promotional campaign a while back. Commercial Analytics was at the table with us throughout the discussion and would engage with us in debate. Then they would do analysis to answer key questions. Having them be part of the team is a real competitive advantage for us.
Reasons for the Group’s Success
There are undoubtedly many reasons why the Commercial Analytics and Decision Sciences group at Merck has been effective. The members of the group certainly have a high level of analytical skills, for example. Another key factor, however, is clearly the culture and relationships orientation in the group. The leadership team of Commercial Analytics emphasizes the key value of the organization:
The umbrella over everything we do is a culture of motivating team members with the prize that we are here to help our clients make better decisions through the use of our analytic insights and tools. Our rules of engagement are to make your internal client understand that you are there to help them make a better business decision.
The cultural orientation begins with clarity about the organization’s mission and responsibilities. The group leader notes:
We’re always objective about our findings. In a way we are the “Switzerland” of marketing and sales at Merck, providing a neutral perspective on those decisions. We work for the shareholders.
The group leader gives an example of how the group’s independence affects its work with internal clients:
A lot of times managers will hear that we can do ROI analysis on promotions. So they come to me and ask if we can help them. I say, “We can do that, but let me ask you a question first. We will find that your promotion was very effective, marginally effective, or ineffective. Can you tell me what actions you’ll take in each of those cases?” We document their answers and how the analytics will tie to them.
The Commercial Analytics’ leadership team refuses to have the group engaged in a project if there is no clear relationship between an analysis and the decision to be made.
The group’s strategy execution client confirms this approach:
Commercial Analytics always has the question of “How’s this going to add value to our business?” at the front of their minds. They aren’t chasing stuff as an academic exercise; they do a good job of checking to make sure that what they are about to tackle has business value. They ask, “What are you trying to get at? Maybe there is a better way to get there.” I don’t think it bothers anyone when they push back a little—they do it in a nice way.
One of the reasons that the group can work successfully with business decision-makers is its emphasis on clear and nontechnical communication about its work. Many of the analyses it undertakes are technically complex, but the Commercial Analytics leadership team devotes considerable effort to translating them into straightforward business terms. The group’s leader describes this process:
We work hard at packaging our results in a way that is very intuitive and easy to digest for our business clients. If an analysis is not understandable to our client, then we failed to provide the appropriate graph, chart, or table. We do not avoid complex methods, but we make sure we can explain them. One of our passions is distilling very complex ideas into simple terms so that business people can understand and apply them.
The executives at Merck we interviewed confirmed that the communications approaches are succeeding. For example, the executive leading the new business area noted:
Commercial Analytics communicates clearly to business-people. They were able to share their methodology with the marketing leaders whose products we are going to be selling. Since those managers are charged with sales force expense, they need to understand and evaluate our pilot.
The strategy execution executive described the communications ability of Commercial Analytics staff in similar terms:
The members of Commercial Analytics didn’t come up through the sales area like I did, but they know they have to translate their findings into something that is “field-friendly.” I know the folks in Commercial Analytics are always thinking about how to do that translation. I have worked with analytical people who are much more academic. It is more effective to work with Commercial Analytics.
Embedding Analyses into Tools
One other approach to improving decisions that the Commercial Analytics and Decision Sciences organization takes is to embed results into small software tools for use by marketing and sales managers in the field. The goal is to help field managers make better decisions by providing decision logic and data for the analyses they typically perform.
The group created a “channel choice simulation tool.” It allows the user—typically the planner of a marketing campaign—to simulate the decision of channel selection for a particular product. The user can play with a variety of scenarios while attempting to optimize the returns on investments across channels. The output of the simulation is a probability of achieving a certain ROI level for a particular product.
Perhaps the most focused analysis tool is one for sales force vacancy management. If a sales rep leaves a particular region, should the manager fill the vacancy? This tool provides qualitative and quantitative analysis to inform the vacancy-filling decision. In a sense, it’s a semiautomated checklist of the factors to consider in filling a sales vacancy. A sales manager’s intuitive feeling about the need for a replacement is a key variable in the analysis.
Future Directions for Commercial Analytics and Decision Sciences
The leader of Commercial Analytics and the interviewed clients all feel that the group is providing considerable value for Merck. The key question going forward involves the direction for role expansion. Should Commercial Analytics, for example, expand beyond the U.S. market and provide support for global sales and marketing decisions? Business across Merck has become considerably more global through both acquisitions and organic growth, and the non-U.S. businesses need more analytical help with sales and marketing decisions. The downside, however, would be the possibility of providing too little support for important decisions in the U.S., which is the largest market at Merck.
Another option for role expansion would involve more “horizontal” collaboration with other analytics groups across Merck. In addition to Commercial Analytics, Merck has strong analytical capabilities in the R&D/clinical area, as well as in health economics and manufacturing. Thus far, the collaborations among these groups have been relatively minimal. Leadership of Commercial Analytics is aware that some other organizations, both within and outside of the pharmaceutical industry, are beginning to view analytics as more of an enterprise-level capability. Thus far, however, the specific benefits of greater collaboration are unclear.
Whatever the future roles of the Commercial Analytics and Decision Sciences organization, the values of independence, clear communications, and assistance to business decision-makers in multiple forms will continue. These cultural attributes are an important component of the group’s success. They have led to a clear competitive advantage for Merck overall and for the executives who have taken advantage of the group’s abilities.