Figure 1: Explanation of Different Touchpoints within a KAM Model; Source Boston Consulting
The move towards key account management in the UK pharmaceutical industry seems to be a response to two long term secular trends; firstly, the rise of the specialty care product at the expense of primary care drugs and secondly, the shift in the balance of power away from individual physicians and towards payers, often involving a whole eco-system of stakeholders in the decision-making process. Thus, a relatively simple set of one to one relationships is being replaced by a complex web of inter-dependencies, with a whole raft of clinical and economic factors to be considered. It is this complexity, involving multiple influences on the decision-making process, that has led many companies to conclude that the simple face to face sales representative should be replaced by a coterie of people, collectively called a Key Account Management system.
While neither of the secular trends above are particularly new popular wisdom seems to accept as true that the majority of companies transitioning towards Key Account Management have been less than fully successful. Some say that the skill set of most traditional field forces is not appropriate for KAM and that the necessary retraining and new hiring will take time. Others say that the payers themselves, particularly in the UK, have yet to agree on a rational decision-making process against a backdrop of incessant budgetary pressure.
A major issue within the pharmaceutical industry is avoiding the “one size fits all” principle and actually identifying which account should be treated as “key”. What are the characteristics of a key account? Are these self-selecting by virtue of their complexity, their potential, the influence already held by the company, a combination of the three or some function of history and time invested to date? In many ways it doesn’t matter what label is attached to an account, rather what is required to deliver to the people that matter an accurate clinical and financial message about the impact that a company’s product has on clinical outcomes and its impact on the account’s budget. Since few companies can actually quantify the impact that each of its touchpoints has on the final decision-making process the tendency is to keep doing what the competition is doing and hope to do it better. However, there is a more rational way to approach this.
From first principles most commentators would agree that successful KAM is about meeting the long term needs of the Key Account (its staff, patients and accountants) by getting the best aggregate clinical outcomes for the least cost. From the pharmaceutical company point of view that cost includes the human and financial resources devoted to managing the account in addition to the cost of goods of the product it sells. To optimize the input costs surely requires that the Key Account Manager understands not only the costs of each of the touchpoints with his/her account but also the contribution they each make to the eventual clinical decision to prescribe the company’s product. Total costs can be calculated based on allocating FTE salaries and expenses but this approach does not analyse the effectiveness of each input i.e. is the contact between employee X and doctor Y having any influence on the decision to give my product first position in the treatment pathway? If not, why not? Is the employee ineffective or the doctor simply irrelevant to the treatment decision?
Each of these impacts can be teased out using modern statistical methodologies, giving each Key Account Manager not only an accurate P&L for each account but the tools to improve that P&L by dialing up or down the inputs with the greatest influence on the clinical decisions that lead to successful treatment. If this sounds cynical let’s not forget that money wasted in today’s healthcare system, even by the pharmaceutical industry, is money that cannot be spent on lowering prices or treating more patients. There is no excuse for a wasteful spending strategy that throws the spaghetti at the wall and waits to see what sticks. The company that properly addresses this issue will not only gain competitive advantage but add significant value to the entire healthcare ecosystem; eliminating waste, in whatever form, should be a priority for all. Payers, especially hard-stretched NHS organizations can claim poverty but pharmacos have no budgetary excuse for avoiding such a modest upfront investment that would benefit everyone.
The author was a Pharmaceutical Analyst at Lehman Brothers for 23 years as well as being involved with the PharmaFutures projects www.pharmafutures.org but is now writing independently. Stewart Adkins also “carried the bag” for Dista Products (Lilly Industries )in the early 1980s. Currently, Stewart Adkins is a Director of Pharmaforensic Limited www.pharmaforensic.co.uk and runs his own consultancy Stewart Adkins Advisors Limited.
If the topics discussed at the most recent Data Science for Pharma conference http://hansonwade.com/events/data-science/ are any guide then a wealth of exciting opportunities lie ahead for the pharma sector to exploit. However, the impression I received was that Big Pharma was behind the curve when it came to the speed and power of the hardware/software combinations being used compared with those routinely available in the financial sector. One presentation in particular, from a Purdue Pharma Data Scientist formerly involved with high frequency trading in the hedge fund industry, demonstrated how he had adapted off-the-shelf kit from investment banking to the pharma industry. He neatly showed how he had created a system (quickly and cheaply, with limited need for maintenance) that could interrogate hundreds of thousands of spreadsheets and documents, including text mining of clinical papers, to generate useful information in seconds – allowing him to respond to high level requests from FDA or his own board members almost immediately. During the coffee break there was some discussion about the relevance of such speed within the pharmaceutical industry but I wonder whether this misses the point. Is there a danger that the “not invented here syndrome” applies equally well to the adoption of new technology as it did to the search for new compounds outside one’s own R&D departments in the 1980s and early 90s? Many companies in that era demonstrated a self-belief that belied their abilities to master the science, with significant lack of competitive edge and at times corporate failure being the end result.
As an occasional voyeur rather than an expert in this field I came away from this conference feeling excited but also puzzled. Would legacy systems and an obsession with process, rather than output, delay or even obscure the benefits that Data Science can bring this industry?
The author was a Pharmaceutical Analyst at Lehman Brothers for 23 years as well as being involved with the PharmaFutures projects www.pharmafutures.org but is now writing independently. Stewart Adkins is a Director of Pharmaforensic Limited www.pharmaforensic.co.uk
Stewart Adkins was a Pharmaceutical Analyst at Lehman Brothers for 23 years and was involved with the Pharmafutures projects.