A leading business process software company sells a cloud platform that large enterprises use to analyze and improve operations such as procurement, accounts payable and order management. It scored the health of its customer accounts on three dimensions, adoption, value and sponsorship, and flagged accounts in red or yellow as at risk of churn. The scores showed which accounts were in trouble. They did not explain what sat behind the trouble or what would keep a customer.
In spring 2024 the company wanted candid answers from the people who own the platform inside customer organizations: the leads who run its centers of excellence and the executives who sponsor the business case. It needed to know whether customers saw a positive return and how long it took, what blocked wider adoption, how well its teams supported customers, and whether new capabilities on its roadmap, including AI features, would weigh on the decision to continue. Respondents could not know who sponsored the research, so that they would speak freely.
PP&A built the interview guide with the client over seven drafts between May and July 2024, starting from the client's own brief. The guide followed the client's health model. An introduction established each respondent's role, use cases and expectations. Sections on value, adoption and sponsorship probed return on investment and how customers measured it, data integration and pre-built content, enablement and operating model, and executive buy-in. A closing section asked respondents to rate five roadmap capabilities on a 1-5 scale for their influence on the decision to continue. The client also shared its reference operating models for customer centers of excellence, from a single-team pilot to a federated structure, as background.
In early August 2024 PP&A conducted three in-depth interviews with customer decision makers: the global head of a business process improvement team who selects the tools, the head of a process improvement center of excellence three years into its deployment, and a former digital transformation director who had led two implementation rounds. PP&A cleaned the call transcripts, extracted the key points by section and consolidated them into an interview-by-interview notes workbook with closing takeaways for each account.
The client received a structured findings workbook covering three accounts in very different condition. All three rated the core product highly for process analysis. The risk sat elsewhere.
The healthiest account had taken a year to show benefits. It then moved from modeling whole processes to narrow use cases on a four-month return cycle, measured in cost reduction and working capital, with savings from established use cases funding new ones. Its main challenge was persuading business units to adopt a complex, expensive tool, made harder by a lack of industry examples beyond core finance and procurement processes and by a licensing model it found hard to understand.
The weakest account showed how value slips away. The client's team spent three months setting up data and validating the business case, but the scope widened toward broad reporting, leadership changed several times, and the organization never made the process changes needed to bank the savings. The former director's advice was to settle ownership first, fix data quality, and start small with a clear return.
The third account treated the platform as its first choice for fully digitized processes, yet data-volume limits and cost pushed some use cases to other tools, and it rated the solution about 70 percent effective for its needs. It found support strong during implementation and thin afterward: weekly emails and no assigned developer, where other vendors sent developers to solve problems alongside the customer.
On the roadmap, a new data layer linking related processes scored 5 of 5 with two of the three respondents, workflow orchestration scored 2 to 3, and two rated the process-modeling suite 1 of 5. Across the three accounts, the risk to renewal came mainly from how value was scoped, proven and supported after go-live, with data-volume limits the one product gap raised.
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