Growth & Management Strategies

Strong foundations before growth architecture

Successful scale-ups have strong foundations. Without them - leadership, culture, strategy, systems, and human capital - a scaling venture is a house of cards. With strong foundations in place, a scale-up can develop its growth architecture: a web of human, financial, technological, and systems capabilities that enables it to grow and survive the inevitable storms.

The structural foundation for this claim sits in the resource-based view of the firm. Jay Barney's paper "Firm Resources and Sustained Competitive Advantage" established the analytical framework: durable firm advantage derives not from market position but from accumulated firm-internal resources that competitors cannot easily replicate - resources that are valuable, rare, imperfectly imitable, and non-substitutable. The substantive treatment of management practice variation as the most empirically supported example of such a resource is treated in What AI changes about African scaling, From Structure to Operations, and Pre-determining Attributes; the implication for scaling strategy is direct. The foundations the live ecosystem debate often treats as administrative overhead - culture, systems, codified processes, accumulated operational routines - are the firm-internal resources that produce sustained scaling capability. They are not what comes after growth strategy; they are what makes growth strategy executable.

The substantive treatment of the operational-tooling architecture this argument implies sits in From Structure to Operations; the operational evidence base on what such tooling produces empirically - including the Indian textile RCT and the long-term Colombian group-consulting follow-up - sits in (Stalled) Acceleration. The implication for growth strategy is that the foundational management practices, codified decision architectures, and organisational routines that produce scaling capability are the most important growth strategy investments African scaling ventures can make. They are also the least visible to investors evaluating a Series A pitch and the least incentivised within the donor-funded ESO architecture.

The EADC's Building a Path to Scale report - synthesising scale diagnostics findings across Kenya, Ethiopia, and Rwanda using the ScaleUpNation methodology and the Argidius SCALE toolkit - identifies the organisational foundation challenge as primary: ventures must replicate their business model at scale, which requires strategic focus on organisational design, talent management, and culture-building. Most current acceleration programmes are not designed to support this transition.

African ventures face strategic choices that are not reducible to standard emerging-market strategy. Three characteristics distinguish ventures most likely to thrive: a focus on underserved mass-market consumers rather than elite segments; control over factors of production and supply chain; and innovation in distribution rather than products.

The structural foundation for understanding why these strategic choices matter sits in the institutional voids literature. Tarun Khanna and Krishna Palepu's Winning in Emerging Markets - drawing on their broader Harvard Business School research programme on emerging-market strategy - established the analytical framework that has done more than any other to explain why developed-economy strategy templates fail in emerging-economy contexts. Their central insight: emerging markets are not characterised by the absence of intermediary institutions (capital markets, contract enforcement, market information, regulatory predictability, talent intermediaries) but by voids in those institutions that firms operating in those markets must fill themselves. Successful emerging-market firms succeed not despite the institutional voids but because they build internal capabilities to fill them - capabilities that competitors who operate in stronger institutional environments do not need to develop and cannot easily replicate.

The Khanna-Palepu framework names the structural reason why African scaling strategy is distinct. The institutional voids African ventures operate against - unreliable power, fragmented payment infrastructure, weak contract enforcement, capital market gaps, regulatory unpredictability, talent-pool depth - are not background conditions that scaling strategy must adapt to. They are the conditions that define the strategic-choice space. Ventures that succeed do so by building the capabilities the voids demand. Ventures that fail do so by importing strategy templates calibrated to institutional environments that do not exist in the markets they are operating in.

The substantive treatment of market-creating innovation as the strategic posture this institutional-voids context produces sits in Defining Scale and Scale DNA; the implication for growth strategy is that large, profitable opportunities in Africa are more likely to be created by deploying well-understood business models in poorly understood markets than by relying on frontier technology and novel innovation. The ingenuity lies in the application, adaptation, and combination of existing approaches - and in the institutional-voids-filling capabilities the application requires.

Growth Teams' research on government capability and sector development makes the same argument at the systemic level. Their Export Boom Atlas - documenting 82 cases of rapid export growth across emerging economies since 1995 - shows what scaling looks like when embedded in sector strategy. Morocco's automotive sector grew from less than 0.1 percent of GDP in 1995 to over 20 percent by 2022, creating 200,000 jobs, through deliberate government policy, anchor investor attraction, and technical training that seeded capabilities across the sector. The playbooks - public leadership, pioneering firms, and external catalysts operating in concert - map directly to what the most successful African tech scale-ups have achieved when all three elements aligned.

Faster-growing firms are almost twice as likely to innovate as slow-growing ones. In Africa's case, this is largely to fulfil unmet consumer needs rather than to create discretionary demand - addressing missing infrastructure, unreliable supply chains, and absent financial services, rather than competing for existing wallet share. The Khanna-Palepu institutional-voids framework names what this innovation pattern is structurally: institutional-voids-filling capability development, rebranded as innovation by venture-finance vocabulary.

AI has introduced a significant new dimension to innovation strategy. The substantive treatment of AI as competitive moat sits in What AI changes about African scaling, Who Captures Value, and Scale DNA Factor 3; the implication for growth strategy is that the ventures building genuine competitive advantages are those using AI not just as a productivity tool but as an intelligence layer - enabling customer segmentation, credit scoring, supply chain optimisation, and fraud detection at a level of contextual specificity that generic global AI tools cannot match. Building proprietary data assets and fine-tuned models for African market conditions is the AI-era equivalent of the institutional-voids-filling capability that has always distinguished durable African scaling. The data moat takes years to accumulate, and it is the operational form of the resource-based-view advantage Barney identified four decades ago.

“If you're building a Nigerian business - a market where electricity, internet, water can be limited - all these fundamentals are not a guarantee for tomorrow. So it’s going to take a bit longer. This isn’t because the business model is bad. It's not that you shouldn't be doing what you're doing. It’s the context in which you’re operating.” - interviewee

Because enabling infrastructure is absent or unreliable in most African contexts, pioneering scaling ventures often need to operate as vertical stack builders - developing both the product or service and the enabling infrastructure that underpins it. The result is complex internal role structures and portfolios of specialisations that would be considered inefficient in more developed markets but are operationally rational in African ones.

The structural mechanic underlying this pattern is named precisely in transaction-cost economics. Oliver Williamson's The Economic Institutions of Capitalism - recognised in his 2009 Nobel Prize in Economic Sciences (jointly with Elinor Ostrom) - established that firms vertically integrate when the transaction costs of relying on external markets exceed the costs of internal coordination. Williamson's empirical pattern: vertical integration concentrates in environments with weak contract enforcement, asset specificity, and information asymmetries - precisely the conditions Khanna and Palepu's institutional-voids framework names as characteristic of emerging markets. African scaling ventures vertically integrate because the transaction costs of relying on missing or unreliable infrastructure exceed the costs of building it internally. The integration is not an inefficiency. It is the rational response to the institutional environment.

The discipline of running such an architecture has academic foundation.Steven Spear and H. Kent Bowen's Harvard Business Review paper "Decoding the DNA of the Toyota Production System" established the analytical framework that has organised the operations-management literature since. Their central insight, drawn from years of embedded research inside Toyota's plants: what produces operational excellence is not the machinery or the process maps but the codified, explicit, continuously improving rules that govern every recurring operation - rules about how work flows, how connections between operations are specified, how problems get surfaced and addressed in the moment they occur. The implication for African vertical-stack operators is direct. Vertical integration creates the surface area for operational complexity that codified operational discipline must address. The African scaling ventures that have successfully integrated vertically - running the full stack across product, infrastructure, distribution, customer relationships, and regulatory engagement - have done so by building the codification discipline Spear and Bowen describe. The ventures that have integrated vertically without the codification discipline have produced exactly the operational fragility the correction period exposed.

The Tolaram model in Nigeria - where building Indomie noodle distribution required pulling in electricity generation, waste management, water treatment, and a comprehensive logistics network - remains the canonical example of what full-stack vertical integration looks like over a thirty-year horizon. Most scaling ventures do not have that luxury. But the principle - that market creation in Africa sometimes requires infrastructure creation first - remains central to scaling strategy. The substantive treatment of the contemporary cases (Moniepoint's last-mile payment infrastructure, Wasoko's end-to-end supply chain) sits in Scale DNA Factor 2 (scalable models) and Scaling Pathways (camel pattern); the implication for strategy is that vertical stack logic applies to tech-native businesses as fully as to consumer goods conglomerates, and the operational discipline it requires is the same.

Building horizontally - offering related business models that reinforce a core offering - is common, especially in technology firms. The structural mechanic at work is the resource-based-view argument extended to multiple business lines: the firm-internal resources (data, customer relationships, distribution infrastructure, regulatory licences, brand) that produce competitive advantage in the original line of business become the foundation for additional lines that competitors lacking those resources cannot enter on equal terms. Successful horizontal diversification is therefore disciplined by the resource architecture of the core, not by the apparent adjacency of new opportunities.

M-PESA's evolution from mobile payments into M-Shwari savings, Fuliza overdraft, M-Akiba government bonds, and M-PESA Global international transfers illustrates the model at its most mature: each product is enabled by the same customer relationship and transaction data while serving a distinct financial need that competitors cannot easily replicate without the same underlying infrastructure. The substantive treatment of platform-economic dynamics sits in Platform Models; the implication for horizontal diversification specifically is the structural finding that the discipline holds when the new product can be underwritten by the same proprietary data assets and customer relationships as the original.

Egypt's MNT-Halan illustrates the same logic in a non-bank financial services architecture. Holding the first independent electronic wallet licence from the Central Bank of Egypt and microfinance, consumer finance, and nano finance licences from the Financial Regulatory Authority - rather than a banking licence - the company built a single super-app across lending, payments, prepaid cards, savings, investments, and e-commerce, all underwritten by its proprietary core banking system Neuron. Cumulative disbursements have exceeded $11 billion since inception; the gross loan book stood at over $1.7 billion across Egypt, Turkey, Pakistan, and the UAE by late 2025. The horizontal expansion is disciplined: each new product is built on the same customer underwriting relationship and the same proprietary technology stack.

The pattern is consistent: horizontal expansion succeeds where it is disciplined by a unified customer relationship and the proprietary data and technology infrastructure that relationship generates. It fails where it becomes opportunistic adjacency - new product lines whose only connection to the core is the same brand. The expansion is coherent when it responds to the structural reality that single-vertical businesses in fragmented, infrastructure-weak markets face inherent margin constraints. Blending vertical and horizontal diversification can create moats that competitors find genuinely difficult to copy.

"The other aspect is governance, and best practice around this, which will help them raise capital and increase their sustainability." - interviewee

Governance has moved from best-practice recommendation to market requirement since 2022. The substantive treatment of governance restructure as a scaling inflection-point decision sits in The Scaling Decision Log Decision 3 - anchored in Hermalin & Weisbach on boards as endogenous institutions, the King IV Code in South Africa, the Nigerian Corporate Governance Code 2018, and the Adams/Hermalin/Weisbach JEL survey on board-effects empirical evidence. The implication for growth strategy is that development finance institutions including the IFC, British International Investment, and Proparco now require credible governance frameworks, board diversity, ESG reporting, and management system documentation as conditions of investment, not preferences.

The Flutterwave governance episode of 2022 - allegations of financial misconduct, insider trading, and workplace harassment against its CEO, reported by TechCabal and subsequently by Rest of World - served as the clearest ecosystem moment in this shift. The broader response has been positive: governance expectations across the investor community have risen, and due diligence on culture and management practices has deepened.

Practical governance discipline for African scaling ventures: choose board composition for the knowledge the organisation needs at its current phase, not for investor comfort. Maintain the right balance between investor board members and independent members with sector and market knowledge - the correction period demonstrated repeatedly that boards dominated by investors optimising for the next round did not catch the unit economics failures that preceded venture closures. Governance is not overhead. It is the resource-based-view advantage at the institutional layer: the firm-internal capability to make consequential decisions well, repeatedly, at the moments when the venture's trajectory is determined more by decision quality than by daily operational performance.