The debate between shareholder primacy and stakeholder theory concerns the legal obligations of corporate directors. Introduction A corporation is never just a machine for making money. It is a legal institution, a social system, and a vehicle for allocating power, risk, and responsibility. That is why one of the most important debates in corporate governance continues to divide scholars, executives, regulators, and investors: should corporations exist primarily to maximize shareholder value, or should they balance the interests of all the people and institutions affected by their actions? This debate is commonly framed as shareholder primacy vs. stakeholder theory. Shareholder primacy says the corporation's central obligation is to its owners, the shareholders. Stakeholder theory says the corporation owes duties to a wider circle of affected parties, including employees, customers, suppliers, creditors, communities, and sometimes society at large. This is not a purely academ...
Emerging-market project management is examined here as a set of disciplines applied under a different distribution of institutional, financial, and regulatory risk. This post considers the structural constraints documented in African infrastructure claims and disputes, the development-sector delivery model, and the Safaricom M-PESA rollout as a documented case of adaptive delivery. The central argument is that the core disciplines of project management remain applicable while the materiality of particular risks can vary by context.
By Kateule Sydney — Researcher and Writer | Last Fact-Checked: 2026-10-05 | Published by Kat-Syd Resources Hub
Emerging-market delivery involves the same fundamental disciplines, with greater attention to institutional capacity, site access, payment security, regulatory uncertainty, and local stakeholder relationships.
Table of Contents
The Structural Constraints of Emerging-Market Delivery
Project management in emerging markets is often discussed in terms of constraints that can make delivery more difficult or less predictable than in highly developed institutional environments. Those constraints can be significant, but it would be too broad to conclude that emerging-market project management is a fundamentally separate discipline.
A more defensible position is that the core disciplines of project management remain applicable, while the distribution and materiality of particular risks can vary by context.
The Project Management Institute’s Pulse of the Profession 2026 provides useful context. PMI reports that 97% of project professionals managed at least one complex project during the previous year, with more than half classifying those projects as significantly complex. PMI also reports that 31% of complex projects fail to achieve the full scope of their originally intended benefits, compared with 12% in its 2024 Maximizing Project Success research. PMI identifies organizational, environmental, and human factors as important sources of complexity, including unclear governance, siloed teams, regulatory volatility, geopolitical instability, and competing stakeholder interests.
These figures are global findings, not evidence that emerging markets perform worse than developed markets. PMI’s research does not establish such a regional comparison. Its relevance to emerging-market delivery is that several of the complexity factors it identifies can become particularly important where institutional capacity, infrastructure, regulation, financing, or service networks are less predictable.
The more useful framing is therefore one of risk distribution.
Emerging-market delivery involves the same fundamental disciplines — scope, schedule, cost, quality, procurement, stakeholder management, risk management, governance, and benefits realization — but project teams may need to give greater attention to risks involving institutional capacity, site access, payment security, regulatory uncertainty, local stakeholder relationships, infrastructure availability, and market conditions.
The practical question is not whether a risk originates inside or outside the project organization. The relevant question is whether the condition can materially affect the project’s schedule, cost, scope, quality, or intended benefits. For the structural causes of project failure that appear across different project environments, see my post on Why Large Projects Fail: The Structural Causes.
African Infrastructure: What the Dispute Data Shows
One useful source for examining infrastructure-delivery risk in Africa is HKA’s CRUX research programme. CRUX analyses claims and disputes arising from major engineering and construction projects. It is therefore important to interpret the data correctly: CRUX is not a survey of every infrastructure project in Africa. It provides evidence about the causes and consequences of claims and disputes within the projects represented in its database.
HKA’s regional analysis has identified significant differences in the causes and effects of claims across regions. In its Africa analysis, restrictions on site access, payment issues, and contract-related claims are among the issues highlighted as important contributors to project disputes and claims. HKA’s more recent CRUX reporting continues to identify access and payment as important areas of concern in African projects.
The significance of this evidence is not that African projects are inherently poorly managed. Such a conclusion would go beyond what the CRUX data can establish.
A more defensible interpretation is that projects represented in the dataset can face substantial exposure to conditions involving access, payment, scope, design, contract management, approvals, and other factors that can translate into claims and delays.
This distinction matters because a claim is not necessarily the same thing as a final loss. A claimed extension of time is not automatically an actual final delay, and a claimed cost is not necessarily an amount ultimately awarded or paid. CRUX is most useful as evidence about where disputes and claims arise and what underlying conditions contribute to them.
The project-management implication is nevertheless important.
If access to a site depends on land acquisition, permits, third-party approvals, community agreements, or other conditions outside the immediate control of the contractor, those conditions should be recognised during planning rather than treated as administrative matters that can be resolved later.
The same principle applies to payment. Where project cash flow depends on government payments, donor disbursements, financing arrangements, or complex contractual payment chains, payment conditions can become delivery risks because delayed payment can affect mobilisation, procurement, subcontractor payments, and progress.
The appropriate response is not to assume that these risks will occur. It is to identify them, assign responsibility, establish monitoring indicators, and develop contingencies where their potential impact justifies doing so. For the wider set of practices that address delivery risk, including forecasting and scaling methods, see my post on Advanced Project Management Practice.
Development-Sector Delivery: A Different Set of Assumptions
Development-sector project management has characteristics that can affect both delivery and the definition of success.
Development projects may be financed through grants, concessional finance, public resources, or combinations of these. They may also be subject to government, donor, or development-partner accountability requirements. Most importantly, their ultimate outcomes may depend on economic, social, institutional, and behavioural changes that extend beyond the project’s formal implementation period.
World Bank evaluations illustrate why local institutional and social conditions matter.
The World Bank’s evaluation of assistance to Albania included examples of projects in which locally adapted approaches produced strong results. One rural poverty-alleviation initiative used village-level credit structures and achieved high repayment rates. The same evaluation found that some rural-works interventions produced less effect on employment and income among poorer groups than had been expected. The evaluation identified contextual and implementation factors that contributed to these differences.
The broader lesson should be stated carefully.
A project design should be tested against the institutions, capabilities, incentives, resources, and social structures that actually exist in the implementation environment.
A project that assumes a functioning land registry, reliable payment mechanism, enforceable contractual arrangements, adequate technical capacity, or predictable administrative approvals where those conditions are uncertain has introduced a delivery assumption that may require active risk management.
Development projects also present a measurement challenge. A project can directly deliver outputs — such as infrastructure, training, financing, equipment, or institutional reforms — while the ultimate development outcome depends on many additional factors. Project monitoring should therefore distinguish between what the project directly delivers and the broader outcomes to which it may contribute.
The implication for project managers is that institutional fit is a project-design issue, not merely a stakeholder-management issue. For the estimation and governance failures that recur in large public projects, see my post on Documented Project Failures and the Estimation Problem.
The M-PESA Case: Adaptive Delivery Under Constraint
The development of M-PESA in Kenya provides a well-documented case of adaptive delivery under local market and institutional conditions.
M-PESA was developed by Vodafone and launched commercially by its Kenyan affiliate, Safaricom, in March 2007. The initial concept was connected to microfinance: the project explored how mobile technology could facilitate payments and repayments for microfinance customers. Development was supported in part by funding from the UK’s Department for International Development.
The important project-management lesson emerged during the pilot.
The system was initially designed around a relatively narrow microfinance use case. During the pilot, however, users began using the service for general money transfers. The project team recognised that actual user behaviour indicated a broader opportunity and changed the direction of the service.
This was not simply a technological adjustment. It was a change in the underlying use case and value proposition.
M-PESA subsequently developed into a mobile-money service that allowed customers to hold electronic value, transfer money, and conduct other transactions using ordinary mobile phones. Customers registered through authorised retail outlets, while agents provided cash-in and cash-out services. The system used a SIM-resident application, with transactions authorised and recorded using secure SMS.
This design was significant because it did not require customers to own smartphones or use conventional bank branches.
The agent model was equally important. Instead of relying on a traditional branch network, M-PESA used retail outlets to support cash deposits and withdrawals. This created a distribution mechanism suited to the existing environment.
Safaricom’s existing market position also contributed to the conditions for rapid expansion. MIT CISR reports that Safaricom had approximately 70% of Kenya’s mobile market in 2007 and that the M-PESA agent network expanded from approximately 350 outlets to 28,000 retail outlets within four years.
The evidence therefore does not support a simple claim that M-PESA succeeded because of one innovative idea.
Its development involved several interacting factors: an identifiable consumer need; adaptation of the original concept following pilot experience; a technology accessible through ordinary mobile phones; a distribution model using retail agents; Safaricom’s existing customer and distribution base; collaboration among commercial, technical, and regulatory stakeholders; and continued adaptation as the service developed.
The strongest project-management lesson is therefore about learning.
The pilot was not treated merely as a test of whether the original plan could be executed. It also generated evidence about what customers actually wanted. When that evidence differed from the initial assumption, the project direction changed.
This is a general project-management principle: plans are valuable, but evidence from implementation can justify changing the plan. For the sector-specific practices that shape how projects are delivered across industries, see my post on Project Management Across Sectors.
Why Replication Produced a Different Outcome in Tanzania
The comparison between M-PESA in Kenya and Tanzania provides a useful case for examining the risks of transferring a successful model from one market to another.
Vodafone introduced M-PESA in Tanzania after the Kenyan launch, but the service did not achieve comparable growth or impact. MIT CISR’s analysis identifies differences in consumer need, infrastructure, and the regulatory environment, as well as differences in the strategies used to introduce the service.
Consumer need. The Kenyan service benefited from a strong existing need for transferring money between urban workers and family members in rural areas. The “Send Money Home” proposition therefore addressed a recognisable problem for a large potential customer base. MIT CISR reports that the same proposition did not resonate as strongly in Tanzania, where historical patterns of rural-to-urban migration were different.
The lesson is not that Tanzania lacked demand for mobile money. Rather, the specific value proposition that had worked in Kenya could not simply be assumed to have the same relevance in Tanzania.
Infrastructure and market position. The market positions of the mobile operators were also different. MIT CISR reports that Safaricom held approximately 70% of the Kenyan mobile market in 2007 and had a large distribution network. In Tanzania, Vodacom had approximately 41% subscriber market share at the time of the M-PESA launch and had a much smaller agent network, concentrated largely in urban areas.
The comparison illustrates an important delivery principle: a distribution model that works in one market may depend on market share, existing infrastructure, geographic coverage, agent capability, and customer relationships that do not exist elsewhere.
Regulatory environment. The regulatory environments were also different. MIT CISR reports that Kenyan regulators worked closely with Safaricom, learning from the early experience and formalising regulations later. In Tanzania, the central bank approved the service without stringent regulations, but the relationship with Vodacom was less collaborative and additional monitoring was required. MIT CISR also identifies the absence of a national identification system as a factor that made customer registration and transaction authorisation more cumbersome.
These differences illustrate why regulatory context should be assessed as part of project planning rather than treated as a background condition.
Exploration versus replication. The most important difference identified by MIT CISR concerns the implementation strategy. In Kenya, Vodafone used pilots, worked with local organisations, and adapted the service as it learned from actual use. In Tanzania, Vodafone relied more heavily on replicating the Kenyan model and managed the implementation from Europe rather than undertaking the same level of local experimentation before rollout.
This does not establish that replication always fails or that exploration always succeeds.
It demonstrates a narrower proposition: when important market and institutional conditions differ, transferring a previously successful model without sufficiently testing local assumptions can produce a different outcome from the original implementation.
That is particularly relevant to emerging-market project delivery because neighbouring countries can appear similar while differing significantly in consumer behaviour, institutional arrangements, infrastructure, regulation, and distribution capacity.
Conclusion
Emerging-market project management does not need to be treated as a completely separate project-management discipline.
The core disciplines remain the same. What can change is the distribution and materiality of risk.
Evidence from African infrastructure claims and disputes indicates that access, payment, scope, design, and contract-related conditions can be important contributors to project claims and disputes. The evidence should not be interpreted as a general measure of African project-management performance because the CRUX database represents projects with claims and disputes rather than every project undertaken across the continent.
Development-sector evaluations likewise demonstrate the importance of fitting project design to local institutional and social conditions. A technically sound intervention can produce different results when the assumptions behind its implementation do not match the environment in which it is delivered.
The M-PESA case provides a particularly clear example of adaptive delivery. The original concept evolved after pilot users demonstrated a different and broader use case. The resulting service combined accessible mobile technology with an agent-based distribution network and benefited from conditions specific to the Kenyan market.
The Tanzania comparison reinforces the importance of context. The Kenyan model was not transferred into an identical environment. Consumer needs, infrastructure, market position, regulatory relationships, and implementation strategy differed.
The practical conclusion is therefore modest but useful: project managers working in emerging-market contexts should identify institutional, access, payment, regulatory, market, and stakeholder conditions that could materially affect delivery and treat them as explicit project assumptions and risks.
In practice, this means:
- Testing critical assumptions before they become embedded in the baseline.
- Identifying dependencies on government agencies, regulators, communities, utilities, land access, or financing.
- Developing realistic contingencies for material external risks.
- Monitoring payment and cash-flow conditions where they can affect delivery.
- Using pilots and early implementation to generate evidence.
- Giving appropriate decision-makers authority to adapt when evidence contradicts the original assumptions.
- Distinguishing documented evidence from interpretation when drawing lessons from individual cases.
The evidence does not show that emerging markets require an entirely different project-management methodology.
It does show that context matters.
The disciplines are broadly the same. The risk profile, institutional environment, and assumptions that must be tested may be different.
That distinction is important because it shifts the focus away from inventing a separate methodology and toward applying established project-management disciplines with greater attention to local conditions, uncertainty, institutional capacity, market needs, payment arrangements, regulatory requirements, and stakeholder relationships.
References
- Project Management Institute. (2026). Pulse of the Profession 2026: Driving Success in Complex Projects: From Navigating Tasks to Navigating Systems. Project Management Institute.
- HKA. (2024). CRUX Insight 2024: Changing the Narrative — An Analysis of Claims and Dispute Causation. HKA Global.
- HKA. (2026). CRUX Insight: From Insight to Foresight — An Analysis of Claims and Dispute Causation. HKA Global.
- World Bank Operations Evaluation Department. (2000). Albania: Country Assistance Evaluation. World Bank.
- Mas, I., & Radcliffe, D. (2010). Mobile Payments Go Viral: M-PESA in Kenya. Bill & Melinda Gates Foundation / World Bank.
- Orlikowski, W., & Barrett, M. (2014). Digital Innovation in Emerging Markets: A Case Study of Mobile Money. MIT Center for Information Systems Research, Research Briefing XIV-6.
- Safaricom. M-PESA historical and corporate materials. Safaricom.
- Vodafone Group. M-PESA: Mobile Money and Digital Financial Services. Vodafone Group.
Read Also on Kat-Syd Resources Hub
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Work Breakdown Structure and the Art of Decomposition — The WBS as a deliverable hierarchy, decomposition rules, common failure modes, and evidence from NASA’s Apollo-era practice and the Denver airport baggage system.
Project Life Cycle: Phases, Gates, and Transitions — Project phases, PMI process groups, phase-gate decision models, and how predictive, adaptive, and hybrid structures distribute project risk.
Written by Kateule Sydney — Researcher and Writer
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