When Harriet Igherighe first walked into the boardroom in early 2019, she faced a room full of hopeful executives and a deal that later became one of the starkest cautionary tales in tech M&A. The acquisition involved a promising fintech startup that offered a cloud-based payments platform, recently valued at over $450 million by eager investors. On paper, the numbers looked pristine: rapid customer growth, sticky subscription revenues, and an enthusiastic forecast for global expansion.
Within eighteen months after the merger, the parent company was writing down nearly 40 percent of the deal’s value. What they had overlooked, and where conventional valuation had failed, was that the startup’s security architecture rested on shared cloud infrastructure, its data-protection policies were thin, and its growth depended heavily on a handful of large clients vulnerable to churn.
A data breach linked to one major client’s misconfiguration triggered customer exodus, regulatory scrutiny, and a cascade of remediation costs. The fintech’s once-promising cash flows evaporated, morale dropped, and what had looked like a win turned into a painful write-off.
It was that fiasco and a dozen others like it that convinced Igherighe of a simple but radical lesson. In today’s technology-driven world, deal valuation can no longer be treated as a static exercise.
Value is not a fixed number; it is fluid, fragile, and shaped by infrastructure, governance, risk, and regulatory tides. She argues that any serious investor or board must stop asking only “What is this company worth today?” and begin asking “How will this value hold up under changing operating conditions and against the full spectrum of technology, regulatory, and cyber risks?”
Igherighe built a career on that philosophy, cutting her teeth first at a global professional services firm and later in the project management office of a major African bank. There she witnessed deal after deal collapse, not because of flawed accounting, but because traditional valuations ignored operational realities.
Forecasts were built on best-case scenarios. Models assumed smooth integration, stable regulation, and sound execution. What they did not assume was cloud-provider concentration, weak identity-management controls, or the potential for cyber incidents, all factors that could erode value far faster than revenue curves suggested.
That experience drove her to reconceive valuation as an integrated system, which she calls a “valuation stack.” At its foundation lies governance: an organization’s risk appetite, internal controls, data-governance practices, and compliance with accounting and capital standards frameworks. Layered above is analytical rigor, including discounted cash flow models, risk-adjusted discount rates, purchase-price allocations, and multi-scenario forecasting. Crowning it all is a robust technology layer, composed of data pipelines, analytics tools, scenario engines, and dashboards that keep models live, traceable, and auditable.
For Igherighe, governance is not a roadblock to commercial ambition. It is a necessary structure for realism. In technology-intensive deals, she maps out critical risks, such as cyber vulnerabilities, vendor concentration, and data privacy exposures, and links them to concrete controls. If a target depends heavily on a single cloud vendor, she builds differentiated revenue and cost projections. If access controls are weak, she computes potential remediation expenses, regulatory fines, or reputational damage. This approach transforms valuation from a static snapshot into a dynamic instrument tied to business reality.
Most dramatically, she reimagines purchase-price allocation. In many corporate transactions, PPA is simply an accounting formality performed post-deal. For her, it is a strategic lens. Intangible assets, such as platforms, customer relationships, algorithms, and brand, often constitute the lion’s share of value in tech firms. Research from the Organisation for Economic Co-operation and Development shows that more than 60 percent of enterprise value in technology companies lies in intangibles. Yet those value drivers are fragile. They depend on operational continuity, market acceptance, regulatory environment, and security integrity.
Igherighe builds PPA models informed not by generic useful-life tables, but by scenario analysis and risk dynamics. In one recent software-as-a-service deal, she stressed the value of platform-related intangibles by modeling potential customer churn driven by regulatory changes, yielding a far more conservative and arguably realistic valuation than the base-case forecast.
She warns that placing faith in a single base case is dangerous. In sectors evolving as fast as fintech, telecoms, and cloud services, the future seldom unfolds in a straight line. To guard against overconfidence, she embeds scenario planning as a default, using tools like Python and R to build engines that generate dozens of valuation outcomes under different assumptions about market demand, regulatory shifts, technology transitions, and operational resilience. The result gives boards a view not just of what could happen, but of how value might behave across different futures and where structural protections, such as covenants or earn-outs, may be needed.
Scenario planning tells them what could happen. Predictive analytics tells them how soon they might see signs. Igherighe’s teams run predictive models to forecast customer churn, usage trends, transaction volumes, and even anomalous behaviors that might signal fraud or operational stress. When those models flag elevated risk for attrition or volatility, she pushes for differentiated assumptions by cohort rather than a single aggregate rate. When analytics suggest that reported growth may not be sustainable, she recommends conservative assumptions or adjusting deal terms. In a recent telecom deal, predictive analytics revealed early signs of partner concentration risk that could undermine future cash flows. The acquirer was able to negotiate mitigation measures and reorder integration priorities before closing.
Igherighe insists that technology does not replace judgement. Rather, it clarifies it.
Tools such as data pipelines, visualization dashboards, and governance frameworks make assumptions explicit, auditable, and communicable. In a typical engagement, the process begins with building a data foundation, extracting operational, financial, and risk data, and cleaning and structuring it. From there, valuation and PPA models are constructed, scenario engines deployed, and predictive analytics applied. Risk and control assessments are mapped back into governance tools. Finally, dashboards, often built in Tableau or Power BI, are used to present the results to boards and risk officers in a transparent, interrogable format.
Over time, Igherighe has codified her methods into playbooks, training materials, and templates. In advisory contexts, her risk-adjusted valuation framework has been adopted across multiple teams. In banking, she helped reposition the project management office from a background function into a strategic partner to the board, anchoring transformation projects in analytics-driven, risk-aware valuation logic. She mentors emerging professionals who want to combine classical valuation skills with advanced analytics and governance tools. Her message is consistent. In a world shaped by rapid technological disruption, volatile regulation, and persistent cyber threats, a strong valuation model is not only mathematically sound, but governed, explainable, and relevant.
She sees even greater challenges. Artificial intelligence is accelerating change, data-protection regimes continue to fragment, and cyber threats are rising worldwide. Ransomware incidents, for example, increased globally by more than 30 percent between 2022 and 2023. In this volatile environment, especially in fast-digitising but regulation-light emerging markets, the need for valuation methods that treat technology as central, governance as foundational, and analytics as the instrument of understanding has never been greater.
Igherighe’s work offers a blueprint for those dealmakers willing to confront complexity head on. It illustrates what high-impact, risk-adjusted valuation can look like: rigorous, transparent, technologically enabled, and sensitive to the many ways value can be eroded when the world changes. For investors navigating both promise and uncertainty, it provides a compass for making smarter decisions in a digital age that rewards realism, resilience, and clarity.
