Markets shift fast, and margin pressure is constant.
Our work focuses on supply chain performance and the pricing strategies that drive growth.
Clients in this sector use data and AI to sharpen decisions across the full business.
A private equity firm had acquired a mid-market B2B technology company with strong fundamentals but inconsistent revenue growth. Twelve months into the hold period, the sales pipeline was active but slow. Reps were spread across too many accounts, and pricing decisions were made on instinct. Deal cycles had also drifted longer than the market warranted. The firm needed a clearer path to revenue acceleration before its planned exit window.
The underlying data existed. Customer records, deal history, pricing variance, and market signals were all available but sitting in separate systems with no shared logic connecting them. Sales leadership had tried reporting tools before, the outputs were informative but not actionable, and adoption had been low. The real need was a system that told reps where to focus and why, during their normal workflow.
Ozaki Consulting started with a focused discovery to map the sales process and identify where decisions were made. The discovery also assessed which data was actually trusted by the team. Rather than building a complex model from the start, the team defined a narrow set of high impact signals: account growth potential, recent engagement patterns, and competitive pricing benchmarks. A lightweight AI model was built to score accounts and generate pricing guidance. It was designed to surface recommendations inside the tools reps already used, with short explanations that connected each suggestion to a business rationale. A pilot ran with a regional team over six weeks. Feedback shaped the interface and the weighting of signals before the solution was rolled out more broadly.
— Pipeline velocity improved by 30% in the first two quarters following full deployment.
— Average deal size grew as pricing guidance helped reps hold position on value rather than discount to close.
— The sales team adopted the tool at a higher rate than any previous technology initiative.
— Leadership attributed this to the simplicity of the interface and the quality of the explanations.
— The private equity firm entered its exit process with a cleaner pipeline story and stronger revenue metrics.
A regional insurance organization had grown steadily over the past decade through acquisitions and product expansion. Operational complexity had grown with it. One core workflow had become a significant drag on speed: the policy change and endorsement process. It touched over a dozen teams and required multiple manual handoffs. The result was a high volume of errors and rework. Leaders knew it was a problem. What they lacked was a clear picture of how the process actually worked end to end, and who owned what.
The process had never been mapped in full. Different teams had different versions of how it was supposed to work, and the actual flow had diverged from documented procedures years earlier. Several automation tools had been purchased over time, but most were underused because the underlying process had never been standardized first. The organization needed to understand the current state before it could design anything better.
Ozaki Consulting facilitated a current state mapping exercise across all teams involved in the workflow. Sessions were structured to surface actual behavior, not stated procedure, which quickly revealed where the real friction sat. Three root causes emerged: unclear ownership at key decision points, redundant review steps that added time without adding value, and a high volume of exception cases that the process treated the same as standard ones. A redesigned workflow was co-created with the teams who owned it. Exception handling was separated from standard processing. Decision rights were clarified. Two full review stages were removed after confirming they added no risk protection. Automation was then applied to the standardized, high-volume steps and then implementation was phased to keep operations running without disruption. A change program ran alongside the technical work, including training, updated role documentation, and a 90-day feedback loop to catch issues early.
— Over 4,000 hours of annual capacity were recovered in the first year.
— Error rates dropped by 35% as the redesigned process removed the handoffs where most mistakes occurred.
— Teams reported higher confidence in the workflow and clearer understanding of their responsibilities.
— The automation investments the organization had already made became significantly more effective once the underlying process was clean.
A financial services firm had completed a significant platform investment. The technology was modern and the content was accurate. The features covered everything customers needed. However, completion rates on key self-service journeys, account updates, document submissions, and service requests, remained stubbornly low. Support call volumes had not dropped as expected after launch. Leadership assumed the issue was awareness, but a marketing push changed nothing.
The instinct was to add more guidance: tutorials, and pop-up prompts. Early testing showed that more guidance made completion rates worse, not better. The platform was not missing information but something about how it was structured was causing customers to stop before finishing. The team needed to understand what was actually happening during the customer journeys.
Ozaki Consulting conducted behavioral research with current platform users. Sessions combined screen recordings and short interviews focused on moments where users paused or abandoned tasks. A clear pattern emerged. The navigation structure reflected the organization's internal logic, not the customer's mental model of what they were trying to do. Customers arriving to update an address, for example, followed a path that matched their goal. Midway through, the journey passed through a section labeled with internal terminology. Customers interpreted this as a different part of the platform and stopped, assuming they had gone somewhere they did not intend to. The fix was precise. Navigation labels were rewritten to reflect customer language. Two journey entry points were consolidated. A single confirmation message was added at the midpoint of longer tasks to signal progress. No backend work was required. The entire change set was implemented in a single sprint.
— Key journey completion increased by 22% within 30 days of release.
— Support call volumes for self-service tasks dropped by 18% in the following quarter.
— The engagement reframed how the product team approached future development.
— Behavioral research became a standard part of the release process.
