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    After I posted my hypothesis that Managed Markets analytics and operational teams were simultaneously more over-whelmed and under-resourced (Blog Series), I had a number of good exchanges with my colleagues, both digitally and IRL.

    Over coffee one day, a client of mine made the offhand comment, “With a name like managed markets, one gets the impression that it’s so orderly. But, it’s not. It’s a complicated mess.”

    He paused to sip his uncomplicated espresso and continued, “Maybe it’s a semantics issue.”

    We had had some fun coming up with organizational names that might garner greater attention by senior management (and greater investment) ranging from the direct (“Mismanaged markets”) to the vaguely literary (“Heartbreaking Markets of Staggering Complexity”) before we got down to a more serious discussion of the factors that make developing operational and analytical processes for managed markets such as challenge.

    While there are undoubtedly more, we honed in on the following:

    • Customer complexity
    • Internal coordination complexity
    • Defining good-better-best
    • Dirty data

    In this post, I’d like to lay out some of the challenges and questions your organization can start addressing across these first three bullet points; the data is “dirty” enough that that bullet point requires a separate post.

    My colleague, who, like many in bio-pharmaceutical sales and marketing, spent a number of years engaged in a variety of roles focused on the “traditional physician customer,” started our exploration of the complexity of managed markets with this, “In my physician world of promotion, everything was just so clean and clear. We had a singular goal – drive sales – and pretty much a singular tool, the sales call, to pretty much a ‘typical’ customer, the physician. We tracked our activity in our CRM, got great & timely data on our product’s and our competitors’ products’ sales. While the sales operations team sometimes went a little crazy on the design of the incentive compensation plans, we still basically knew that if the sales or share trend went in the right direction, everything was golden.”

    As we tried to lay out the differences in complexity when it came to supporting Key Account Managers (KAMs) in the field, the coffee-shop napkins soon became inadequate and I turned to PowerPoint to sketch out this framework of coordination that a KAM needed to manage between the internal ‘partners’ and external customers:

    Being a career consultant, I was quite proud of this framework and thought it captured the complexity sufficiently, but my client didn’t think I had gone far enough.

    “It is much more than that. You’ve captured the customer variety at an organizational level, but what about the functions within each organization? From organization to organization we are dealing with P&T committees, pharmacy directors, quality directors, provider relations and executive management. However, the relative importance of each of these functions varies across organizations. Our CRM tools capture the names, but not the nuances of influence. Our secondary data certainly is not linked to this level of granularity. We just don’t have the level of detail or the linkages that we need to truly map these customers.”

    I could feel that the espresso was having its energizing effect as he continued, “Even if we did map these relationships, we often haven’t taken the time to truly define what we really want as an outcome from a contract or customer relationship. Are we looking just for market share or prescription volume gains? If so, what level of rebates or other discounts are we willing to accept? Do we care just about direct influence within the plan or will we consider spillover impacts into the marketplace? Do we have benchmarks on what has worked in the past? Which of our levers have had what impact? How has that varied by the different customer types? Across different geographies?”

    I was getting concerned that maybe he should’ve stuck to the solo instead of triple espresso as he continued, “And, once we figure all of these answers out, how do we design a performance plan that aligns our KAMs and the rest of our organization to meet both of our customers’ expectations and our financial objectives?”

    Like a good consultant, I responded, “Once we get your data organized, we’ve got a framework to help you answer all of those questions.”

    Next post – Dirty Data, meet the KAM Braintrust

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