Case Study

Sales Force Effectiveness

Data Assessment In Action

Published On

WHAT WILL YOU LEARN

KMK assisted one of its clients with its ophthalmic product launch. Before the engagement, the data had already been purchased by a vendor without any data assessment and was deemed adequate for the pre-launch. However, one-month post-launch it was found that the reported sales volume per vendor was much lower than the client expected. Initially, it was thought that this discrepancy was caused due to data lag but after an additional month of monitoring, reported sales were still off, creating repercussions within the client company.

In this case study, you will get acquainted with the approach taken by KMK’s data management team to resolve the issue. You will explore how our team conducted a comprehensive data quality assessment and took the necessary actions to provide a feasible solution for the client company.

An Ophthalmology Product Launch

Introductions

KMK Consulting was engaged by a pharmaceutical client to assist with the launch of their ophthalmic product.

Before the engagement, data had already been purchased from Vendor A without doing any data assessment. Leadership at the client company was accustomed to working with similar datasets, and assumed the data quality of Vendor A was industry best. The data was deemed adequate for the pre-launch marketing analysis and sales planning, and the product was successfully launched.

One month post-launch, the reported sales volume per Vendor A was much lower than the client expected. For certain territories it was even lower than the total coupons that had been redeemed. Initially, it was thought that this discrepancy was caused by data lag but after an additional month of monitoring, reported sales were still off. The sales team complained that they were not being credited correctly, and company leadership began to worry about overall product performance.

KMK’s data management team believed something was wrong with the data. They contacted Vendor A in an effort to understand what happened and why. At the same time, KMK started to work with a different vendor, Vendor B, asking them for a comparative data sample. After a few weeks of investigation KMK was finally able to understand the root of the problem with Vendor A.

There were two major issues causing the inaccurate sales data. The product was primarily distributed by specialty pharmacies, however, Vendor A’s coverage of specialty pharmacies in this particular market was very poor. Because of this, the majority of the sales volume needed to be predicted. In terms of projection, Vendor A claimed that their project methodology was based on the total market instead of on a few specific products -unless the product sales exceeded a certain volume threshold.

With their market heavily dominated by generic products, such a projection methodology is inappropriate and therefore gave the client results that were not even close to the actuals especially at the physician level.

When KMK received the new data sample from Vendor B and compared the launch-to-date sales volume from Vendor A, the scripts reported by Vendor B were twice those of Vendor A, and much more in line with the coupon data and field feedback. KMK’s team also conducted a comprehensive data assessment to compare the two data vendors and as a result eventually made a decision to terminate the contract with Vendor A all together.

The Result

Ultimately, it took a significant amount of time and money to complete the data transition and have the new data fully reflected in all of the client’s downstream processes. Because the data structure of Vendor B was entirely different than that of Vendor A, the changeover had a large impact on the data warehouse requiring it to be rebuilt in order to accommodate the change. All of the client’s stakeholders needed to present alternative solutions before the data switch could be complete which took a significant amount of effort by the entire organization.

The resulting direct economic impact was more than $200,000 including the cost of the additional work. In terms of the original contract, many negotiations were needed to terminate the relationship with Vendor A and ultimately an early termination fee was incurred by the client. The entire process of switching vendors took about six months during which all operations were slowed down. This caused a loss in trust and demoralization of the sales team, leadership and potentially, investors. Had a data assessment been done initially, all of this could have been avoided.

Want to Learn More?

Are you thinking about data assessment? KMK can help you select and evaluate the best data asset or data provider to support your business and analytical needs – whether it be commercial strategy, market assessment, forecasting, patient journey, operation, and/or RWE. Our skilled team will ensure you understand the advantages and drawbacks for each data asset while providing potential solutions for any shortcomings. Leverage our cross-functional expertise on data re-utilization and see future cost savings!
Contact us at info@kmkconsultinginc.com today to learn more!

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