By Micah Asamba, Director, Keynea Research & Analytics Ltd
More than ten years in research consultancy has taught me that this profession is rarely just about research. It is about solving problems, understanding people, meeting demanding deadlines, adapting to change and, perhaps most importantly, continuously learning.
My journey began long before Keynea Research & Analytics Ltd became the formal business it is today. Over the years, I have worked with students, researchers, academics, professionals, businesses and organisations on projects at very different stages of development. Some clients arrive with little more than an idea. Others come with a nearly completed PhD thesis requiring a final methodological review. There are also organisations looking for evidence to support a programme, strategy or investment decision.
That diversity has shaped the consultant I have become.
From Academic Research to a Much Broader Consultancy Practice
Teaching at university level has also given me the opportunity to experience research from the other side of the desk: as a lecturer, researcher and academic mentor.
Consultancy, however, quickly took me beyond the boundaries of my own academic discipline.
Over the years, my work has involved research proposals, master’s dissertations, doctoral theses, systematic and scoping reviews, journal manuscripts, qualitative studies, quantitative research and mixed-methods projects. I have worked with datasets requiring SPSS, Stata and other analytical approaches, as well as qualitative projects involving interviews, focus groups, transcription, coding and thematic analysis.
Other assignments have involved research instruments, sampling strategies, ethics and regulatory requirements, literature reviews, statistical interpretation, manuscript preparation, journal revisions, policy-oriented research, market and industry analysis, surveys, grant-related work and technical reports.
One lesson emerged quite early: a consultant cannot afford to stop learning.
A client may bring a qualitative study today and a complex quantitative project tomorrow. Another may require a systematic review, while the next needs assistance responding to journal reviewers. The consultant must understand not only how these methods differ, but also when they are appropriate and how they fit within the client’s wider objectives.
Working Across Borders
One of the most interesting developments in my career has been the geographical expansion of my work.
Technology has made it possible to work with clients thousands of kilometres away without ever sharing a physical office. I have handled assignments involving clients and projects in Kenya and elsewhere in Africa, as well as clients based in Europe, Asia and North America.
International consultancy comes with its own lessons.
University requirements differ. Research cultures differ. Referencing systems differ. Expectations around communication, deadlines and document presentation can also vary considerably.
A researcher working within an American doctoral programme may have requirements quite different from those of a postgraduate student at a Kenyan university. A client in Hong Kong may communicate differently from a client in Nairobi. A project involving Somalia or South Sudan may require a different understanding of context from one involving Kenya.
Working across these environments has taught me to listen before prescribing solutions.
The first task is always to understand what the client actually needs.
Work Ethic Has Been My Most Reliable Tool
Consultancy is built on trust.
Clients sometimes hand over work representing several years of their lives. A doctoral thesis, for example, is not simply another Word document. Behind it may be years of coursework, data collection, financial sacrifice, supervisor meetings and personal commitment.
That deserves respect.
I have therefore tried to build my work around a few straightforward principles: understand the assignment properly, communicate clearly, protect confidentiality, meet agreed deadlines, verify work carefully and remain available when revisions are required.
Not every project goes according to plan. Supervisors change their minds. Reviewers request additional analysis. Data arrive late. Clients discover new university requirements shortly before submission. Research designs that appeared straightforward initially sometimes reveal weaknesses during analysis.
Good consultancy requires the willingness to revisit the work rather than defend an approach simply because considerable time has already been invested in it.
Then Came COVID-19
The COVID-19 pandemic was one of the most significant disruptions I encountered during this journey.
Research activities were interrupted. Universities closed or restricted physical access. Face-to-face interviews and fieldwork became difficult. Students and researchers experienced delays that were completely outside their control.
Consultancy itself also changed.
Work that might previously have involved physical meetings had to move online. Documents became the primary means of collaboration. Video meetings, cloud storage and digital communication became normal rather than supplementary.
The pandemic was difficult, but it accelerated a transition that ultimately made the consultancy more flexible.
Geography became less important.
If a research project could be discussed virtually, documents exchanged securely and analysis undertaken digitally, there was little reason that the consultant and client had to be in the same city—or even on the same continent.
That realisation helped shape the online consultancy model I use today.
And Then AI Changed Everything Again
Just as the research community adjusted to remote working, another major disruption arrived: artificial intelligence.
The rapid development of generative AI has probably produced the biggest change in research and professional writing during my consulting career.
My response has not been to resist it.
I have chosen to learn it.
AI can dramatically improve research productivity when used properly. It can assist with organising information, exploring analytical approaches, coding, reviewing documents, identifying inconsistencies and accelerating repetitive tasks. It can also allow a consultant to test alternative approaches much faster than was previously possible.
But speed is not the same as quality.
AI can produce inaccurate information, fabricated references, superficial analysis and confident conclusions unsupported by evidence. A researcher who accepts automated output without checking it can create more problems than the technology solves.
My academic training and years of consulting experience therefore became more valuable, not less valuable, with the arrival of AI.
I increasingly see AI as an additional tool in the researcher’s workspace. Statistical software did not eliminate statisticians. Reference managers did not eliminate researchers. Search engines did not eliminate literature reviews. In the same way, AI does not eliminate the need for methodological knowledge, critical judgement and subject expertise.
The advantage comes from knowing what to automate, what to verify and what requires human judgement.
The Nature of the Work Has Changed
Today’s client often arrives with problems that barely existed several years ago.
They may have a manuscript requiring extensive revision after peer review. They may need to establish whether references are genuine and correctly used. They may have a dissertation containing sections developed with AI assistance that now require careful scholarly review. Another client may need a large qualitative dataset transformed into defensible themes without losing the voices of participants.
This means research consultancy itself must evolve.
My work today involves combining traditional research competencies with newer digital capabilities. The fundamentals remain unchanged: a defensible research problem, appropriate methodology, credible evidence, accurate analysis and conclusions that follow from the findings.
Technology changes how efficiently we reach those outcomes. It does not change what makes the research credible.
The Challenges Have Also Been Real
More than a decade in consultancy does not produce a story consisting entirely of successful projects.
There have been difficult clients, delayed payments, unrealistic deadlines and assignments that expanded considerably after they began. There have been occasions when substantial work had to be redone following supervisor feedback. There are periods when several major deadlines arrive simultaneously and others when business is unexpectedly quiet.
Running a consultancy also means doing considerably more than research.
There is accounting. Tax compliance. Marketing. Contracts. Client acquisition. Websites. Software. Data protection. Record keeping. Quality control. Managing collaborators and consultants. Following up invoices. Keeping up with changing research standards.
I have learned from mistakes in virtually all these areas.
What has mattered is improving the system after each experience.
From Individual Consultant to Keynea Research & Analytics Ltd
One of the important milestones in this journey was formalising the work through Keynea Research & Analytics Ltd.
That transition represents more than registering a company. It reflects a gradual shift from thinking about consultancy as individual assignments towards building an organisation with systems, records, policies, collaborators and a longer-term identity.
The ambition is also broader.
Academic research remains an important part of my work, but research expertise has applications far beyond universities. Businesses need market intelligence. NGOs need programme evidence. Policymakers need credible analysis. Organisations need monitoring and evaluation, surveys, feasibility studies, policy briefs, strategic research and reliable data analysis.
The same fundamental question connects these assignments:
What does the evidence actually tell us?
That is the question I have spent more than a decade helping clients answer.
What Ten Years Have Taught Me
Perhaps the greatest lesson has been that expertise is never finished.
The consultant I was ten years ago could not have anticipated COVID-19, today’s remote-working environment or the extraordinary development of generative AI. I cannot know precisely what research consultancy will look like ten years from now either.
What I can control is the willingness to adapt.
Methods will evolve. Software will change. AI will become more capable. Client expectations will rise. Some services that are valuable today may eventually become automated.
But careful thinking, integrity, reliability, intellectual curiosity and the ability to understand a client’s problem will continue to matter.
I have built my career by combining those principles with continuous learning. From academic research and statistical analysis to international consultancy and now AI-assisted research workflows, each change has added another layer to the experience accumulated along the way.
After more than a decade, I remain convinced of something quite simple:
Good consultancy is not about knowing everything. It is about having the experience to ask the right questions, the discipline to find credible answers, and the integrity to tell a client what the evidence actually supports.
About the Author
Micah Asamba is a researcher, university lecturer and Director of Keynea Research & Analytics Ltd. With more than a decade of experience in research consultancy, his work spans research design, quantitative and qualitative analysis, systematic reviews, academic and scientific writing, journal manuscript development, data analytics and research advisory services. He has supported researchers, professionals and organisations working across different disciplines and geographical regions.
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