Our Work
A selection of engagements across strategy, turnaround, M&A, data, and transformation. Client details anonymized where appropriate to protect confidentiality.
The Challenge
A PE-backed industrial chemicals company was experiencing sustained profitability challenges despite stable demand. Leadership lacked visibility into true unit economics—they didn't know their cost per litre delivered. Pricing decisions were inconsistent, route complexity was poorly understood, and sales optimized for volume over margin.
Our Approach
We built a fully-loaded costing and pricing model that accurately reflected production, logistics, routing, and delivery complexity. We established minimum margin thresholds by customer, route, and product, then reset pricing and sales strategy around delivered economics.
The Challenge
A public acquisition platform pursuing a "Buy, Build, Hold" strategy needed rigorous commercial due diligence for multiple simultaneous industrial acquisitions. Investment committee required validated market assumptions, identified risks, and confidence to proceed.
Our Approach
We led end-to-end diligence programs across three acquisitions, coordinating legal, accounting, and technical advisors. We validated market size, competitive positioning, customer concentration, and revenue quality. We produced IC-ready materials with clear scenario analyses.
The Challenge
A high-growth robotics company had secured large enterprise customers making capital-intensive investments. But execution readiness—product maturity, customer management, organizational structure—wasn't aligned to early-majority enterprise expectations. The gap between innovation and delivery posed significant risk.
Our Approach
We built an integrated strategic platform: an OGSM decomposed into 30+ execution strategies, stress-tested against organizational reality. We designed a customer prioritization model, commercialization roadmaps for flagship accounts, and a 30-60-90 day execution plan.
The Challenge
Traditional analytics couldn't measure human behavior, emotion, and engagement at scale. Organizations across HR, healthcare, insurance, and retail needed real-time, actionable insights from unstructured behavioral signals—video, audio, and text—to make better decisions about people, performance, and well-being.
Our Approach
As co-founders, we built an intelligent human-analytics platform combining proprietary algorithms, patentable IP, and applied data science using a computer vision platform licensed from GE. We developed Intelligent Emotion Scoring™ and Advanced Action Signaling™ engines, and commercialized the technology across various applications including automotive repair, financial services, and HR.
The Challenge
A rapidly growing ag-tech manufacturer needed a fact-based understanding of its competitive position, customer dynamics, and scalability risks. Leadership was making decisions on intuition rather than evidence, with limited visibility into customer concentration, retention, and growth opportunities.
Our Approach
We built customer analytics models analyzing top-20 accounts, estimated market potential using population and penetration metrics, and identified cross-sell and win-back opportunities. We surfaced ecosystem risks related to third-party dependencies and created segmentation views classifying customers by risk and opportunity.
The Challenge
A heavy equipment company needed to improve sales coverage and market penetration in a highly competitive regional market. Territory design was ad hoc, customer engagement was inconsistent, and substantial revenue was being left on the table in underperforming counties.
Our Approach
We analyzed multi-year customer data, segmented accounts by value and behavior, and designed a tiered coverage model with explicit engagement cadences. We built a 52-week customer call plan for every account and modeled sales capacity against coverage expectations.
The Challenge
Following a significant organizational redesign, Corporate Services performance was experienced as inconsistent. Role ambiguity, unclear priorities, and weak accountability mechanisms were reinforcing misalignment. Shadow systems and workarounds were masking deeper systemic issues.
Our Approach
We conducted 42 in-depth interviews across leadership, applied structured qualitative analysis to identify patterns, and used cause-and-effect analysis to surface primary drivers. We developed a practical alignment approach grounded in leadership decision-making and clear accountabilities.
The Challenge
A cargo division lacked a reliable, customer-centric data foundation. Inconsistency in customer identifiers, commodity descriptions, and currencies made it impossible to understand customer performance, market dynamics, and revenue opportunities with confidence.
Our Approach
We normalized currencies, aligned time periods, standardized commodity descriptions to industry standards, and synthesized fragmented customer records. We built flexible, self-serve analytical workbooks enabling commercial leaders to explore customer and commodity performance dynamically.
The Challenge
A regional governing body representing multiple municipal jurisdictions needed to align data ownership, standards, and decision-making processes to enable coordinated planning and funding allocation. Fragmentation in data standards was limiting regional decision-making.
Our Approach
We designed and executed a cross-jurisdictional discovery process, defined a common data vision and principles, and developed a practical delivery model balancing centralized governance with local autonomy. We translated strategic objectives into a concrete cloud integration plan.
The Challenge
A large industrial services company needed more than a strategy refresh—it required a unifying direction, a fact-based view of competitive position, a disciplined execution system, and cultural alignment across a distributed workforce.
Our Approach
We conducted extensive groundwork including financial, utilization, and safety data analysis. We reframed vision and values into executable priorities, implemented OGSM as an enterprise execution system, and diagnosed organizational execution risk using pivot-point analysis before strategies were rolled out.
The Challenge
An arms-length organization stewarding hundreds of millions in public funding operated with minimal internal headcount and heavy reliance on third-party providers. Effectiveness was constrained by how work, authority, and responsibility were fragmented across vendors.
Our Approach
We reconstructed the real operating model, performed invoice-level forensic analysis, stress-tested risk and due-diligence processes against industrial project realities, and quantified efficiency opportunities. We distinguished between renegotiation, restructuring, and vendor replacement options.
The Challenge
A large non-profit had a loyal donor base but fundraising efforts were constrained by limited prioritization, inconsistent data use, and lack of execution tools for fund development officers. The challenge was decision clarity: which donors to focus on and how to allocate limited capacity.
Our Approach
We analyzed a decade of donor data to understand giving behavior, retention, and growth opportunities. We designed a segmentation framework classifying donors by strategic value, quantified realistic revenue potential by segment, and delivered prioritized donor lists for immediate campaign execution.
The Challenge
An industrial services company needed a data-driven growth strategy to enable leadership and the board to make confident decisions around market opportunity, investment, and go-to-market execution. The goal was to identify where they could grow profitably and how to systematically target high-value customers.
Our Approach
We analyzed five years of invoice and customer data to identify revenue concentration, growth patterns, and margin dynamics. We built customer blueprints and ideal customer profiles, then matched highest-value customers to D&B prospect data to identify look-alike prospects. We delivered execution-ready tools enabling sales teams to focus on the right customers.
The Challenge
A multi-generational industrial equipment company needed to validate and formalize a multi-year growth strategy. Leadership wanted to move beyond intuition and legacy assumptions by combining leadership alignment, customer insight, data science, and market analysis to identify credible paths to scale.
Our Approach
We facilitated leadership workshops, conducted customer and supplier interviews, and analyzed years of internal sales and operational data. We evaluated growth scenarios across manufacturing, service, parts, and aftermarket channels, and developed innovation concepts to support future recurring revenue and differentiation.
The Challenge
A major polytechnic's Applied Research division faced systemic operational, financial, and governance challenges. Poor upfront project design, inadequate project management, and lack of real-time data were limiting effectiveness, increasing risk, and undermining confidence among funders and industry partners.
Our Approach
We conducted months-long discovery including interviews, observations, and financial analysis. We assessed how projects were conceived, funded, staffed, and delivered in practice. We diagnosed structural drivers of unprofitability, evaluated the stage-gate process, and developed practical, phased recommendations prioritizing stabilization over reorganization.
The Challenge
A portfolio company was experiencing sustained losses driven by product complexity, pricing opacity, and operational inefficiencies. Management needed to identify the root causes of margin erosion and define a clear, data-driven path back to profitability.
Our Approach
We applied data science to calculate true gross profit at the product and SKU level. We designed a product complexity model to quantify the operational and financial impact of portfolio sprawl, identified products destroying value despite generating revenue, and built dashboards to expose pricing inconsistencies and margin leakage.
We'd welcome the opportunity to learn more about your situation and explore whether we can help.