Data-Driven Business Analysis Recaptures Business from Profitable Product Line

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Sagence’s business analysis services helped a healthcare manufacturer identify areas of lost business by eliminating the ambiguity for the loss and developing a data-driven approach to recapture lost segments.


A large, privately held national manufacturer and distributor of health care supplies was concerned they were losing business in one of their most profitable product lines. Hypotheses ranged from a lack of sales force attention and coverage to product knowledge gaps. They asked Sagence to both measure the size of the opportunity and devise mechanisms for preempting the loss.


Our business analysis started by working with members of the client’s sales, finance, and IT teams to estimate the scale of the opportunity of the client’s two largest customer segments. We collected applicable data including one year’s worth of orders (5M+), product master data, customer master data and validated all of this through comparisons to standard reports and data profiling. We then constructed the analytical dataset by recreating relationships established in the client’s systems, creating relationships where they previously didn’t exist and prepared initial calculations on things like order intervals. Finally we developed an algorithm to identify past loss events, sized the opportunity and supported a reporting mechanism for prompting sales force activity to preempt the loss.


With Sagence’s data-driven business analysis expertise our client is prepared to launch programs to prevent and recapture lost business. The analytical platform Sagence built enables our client to preempt loss and can be refined for predictive analyses so they can remain focused on customer needs.

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Sagence is a management consulting firm advising clients in information-intensive industries. We specialize in data management and analytics and in the acquisition, evaluation, and development of critical data assets. Contact us today to learn how we can help you leverage your data as an asset.