The managing director wants to know why sales are falling.
Sales team says the problem is pricing. Operations blames stock availability. Finance points to delayed customer payments. Marketing says lead generation has actually improved.
Everyone has numbers to support their position. Nobody has the same explanation.
That meeting captures a problem that is becoming increasingly common across African businesses. Organizations are collecting more data than ever, buying more software, and producing more reports, yet many still struggle to answer the questions that matter most.
This is not necessarily a technology problem. The company may already have an accounting system, a CRM, spreadsheets, payment records and several reports. It may even have a business intelligence dashboard.
The problem is more fundamental.
The organization has not built a reliable way to turn data into decisions.
Africa's data problem is not simply a shortage of data
It is tempting to think that the first step toward becoming a data-driven business is to collect more information or buy better technology.
The evidence suggests a more complicated picture.
A 2024 IFC study covering African firms found that 86% of firms had access to basic digital technologies such as mobile phones, computers or the internet. But access did not mean intensive business use. IFC found that only a much smaller proportion of firms used these technologies intensively in their operations, and that businesses making more intensive use of digital technology achieved markedly higher productivity.
That distinction matters.
A company can have internet access without having a digital sales process. It can have accounting software without integrated financial information. It can have customer records without understanding customer behaviour. It can have a dashboard without having a management process built around the information on it.
The World Bank makes a similar point from a broader perspective in its World Development Report 2021: Data for Better Lives. Data can be used by businesses to improve decisions, reduce costs, improve products and create economic value, but data itself does not produce those outcomes. Value comes from the people and organizations that are able to turn data into insight and action.
So the important question for an African business is not:
"How much data do we have?"
It is:
"Which important decisions are we making better because we have this data?"
That is a much harder question.
It is also the more useful one.
The gap between having information and being able to use it
Consider a company with branches in Lagos, Port Harcourt and Abuja.
The company records sales every day. Finance has its accounting records. Each branch maintains operational information. Salespeople keep customer information. Management receives a monthly report.
On paper, the organization appears to be data-rich.
But then the managing director asks a relatively simple question:
Which customers generated the most profitable revenue in the last six months, and which of them are showing signs of declining activity?
Now the organization has a problem.
Revenue may be in the accounting system. Customer information may be maintained by Sales. Product margins may sit with Finance or Operations. Customer activity may be spread across invoices, payment records and individual sales representatives' files.
Someone has to bring these pieces together.
Customer names need to be matched. Duplicates need to be removed. Different definitions have to be reconciled. Missing information has to be investigated.
Eventually, someone produces a spreadsheet.
The report may be useful, but it took several days to produce and may already be out of date.
This is the part of the data conversation that is often overlooked.
The problem is not always the absence of data. Sometimes the problem is the distance between where data is generated and where a decision needs to be made.
The longer that distance becomes, the more expensive data becomes to use.
When every department has its own version of the truth
One of the clearest signs that an organization has a data problem is when different departments can produce different answers to what should be the same question.
Take "revenue."
Finance might use recognized revenue.
Sales might report the value of orders booked.
Management might be looking at cash collected.
None of these numbers is necessarily wrong. They answer different questions.
The problem starts when the organization has not agreed on which definition should be used for which decision.
The same thing happens with "active customer," "profit," "completed project," "stock available," "new customer" and dozens of other measures.
Once definitions become inconsistent, the organization starts spending time debating numbers rather than interpreting them.
This is where data governance becomes more than a compliance exercise.
At the business level, governance is about establishing ownership, definitions, access, quality standards and accountability around important information.
The African Development Bank's 2026 work on data governance makes a related point at a continental level. Africa is generating increasing volumes of data through digital commerce, mobile money, digital identity and other systems, yet institutional fragmentation, limited data sharing, capacity constraints and trust issues can prevent that data from generating its full value.
The same principle applies inside a company.
If information cannot move reliably across the organization, its value is reduced.
The spreadsheet is rarely the real problem
It is fashionable to blame Excel.
That misses the point.
Excel is often the most practical tool available to a business. A competent analyst can use it to explore data, model scenarios and answer important questions.
The problem begins when spreadsheets become the unofficial infrastructure for processes that should have stronger controls.
One person creates the master file. Another downloads a copy. Someone changes a few figures. A manager asks for another version. Another employee combines two files and sends the result through WhatsApp.
Eventually, nobody is completely sure which version is authoritative.
At that point, the problem is not Excel.
It is the absence of a reliable system for managing the information.
The same thing can happen with sophisticated software.
A company can spend heavily on an ERP, CRM or business intelligence platform and still have poor data practices if the underlying processes are inconsistent.
Technology can make a good process faster.
It can also make a bad process operate at greater scale.
A dashboard cannot fix a broken data process.
Why more dashboards do not necessarily make a business more data-driven
This is another trap.
Organizations often respond to information problems by asking for more reports.
Then more dashboards.
Then another dashboard for management.
Then a dashboard for Sales.
Then another one for Operations.
Soon the organization has plenty of visualizations but still struggles to answer basic questions.
The problem is that a dashboard is only useful in relation to a decision.
If a manager sees that sales have fallen by 12%, what happens next?
Who investigates it?
How quickly?
What information do they need?
What action can they take?
When will the result of that action be measured?
Without those connections, the dashboard is simply a more attractive way of displaying information.
The real objective of analytics is not to produce more reports.
It is to reduce the distance between what is happening in the business, understanding why it is happening, and deciding what to do about it.
That is a much higher standard.
The African context makes good data systems even more important
There is no reason African organizations should simply copy data strategies developed for large corporations in Silicon Valley or Europe.
The operating environment is different.
A data strategy designed for a large corporation with standardized processes across twenty countries cannot simply be copied into a growing African business and expected to work.
Many African businesses operate across a mixture of digital and physical channels. Customers may interact through websites, social media, WhatsApp, agents, physical branches and informal relationships. Payments may come through bank transfers, cards, POS terminals and other channels. Branches may also have different levels of digital maturity.
That creates a particular challenge.
The organization may be generating a significant amount of information without generating it in a consistent form.
The answer is not to pretend that these realities do not exist.
It is to design systems around them.
This is one reason the IFC's findings on digital intensity are important. The issue is not simply whether businesses have access to digital technology. The question is whether technology has become sufficiently embedded in the way they actually operate to improve productivity and competitiveness.
For some businesses, that may mean integrating financial and operational systems.
For another, it may mean standardizing customer records.
For another, it may mean moving away from manual reporting.
For another, it may mean establishing clear ownership of data before investing in more advanced analytics.
There is no single technology answer.
There is a business problem to solve first.
Start with decisions, not data
For organizations trying to become more data-driven, I recommend starting with a simple exercise.
This is the shift many organizations need to make.
Instead of asking:
What data can we collect?
Ask:
What decisions do we need to make better?
Start with the decisions that have the greatest effect on the business.
Identify the 10 to 20 decisions that matter most to the business.
Then ask five questions about each one:
What decision are we trying to make?
What information do we currently use?
How reliable is that information?
How quickly can we obtain it?
What would change if we had better information?
This exercise often reveals that the organization's biggest data problems are not where management initially thought they were.
You may discover that the business does not need another dashboard.
It needs better customer data.
Or better inventory records.
Or a consistent definition of revenue.
Or automated data collection.
Or clearer ownership.
Or simply a management process that actually uses the information already available.
That is a much more useful starting point.
If nothing will change regardless of what the data says, there may be no point building another report.
What a data-driven organization looks like
A data-driven organization is not the one with the most dashboards, the largest database or the most expensive software.
It is an organization where important decisions can be supported by information that people understand and trust.
Leadership knows what the important numbers mean.
Teams know where the information comes from.
Data has clear owners.
Problems with data quality can be identified and corrected.
Reports arrive at the frequency the business actually needs.
Analysts spend more time answering meaningful questions and less time repeatedly searching for, cleaning and reconciling basic information.
Most importantly, information changes behaviour.
A manager sees that a branch is underperforming and investigates.
A sales team identifies customers whose activity is declining and responds.
Operations detects a recurring bottleneck and changes the process.
Finance identifies a cost trend before it becomes a serious problem.
Management reviews the result and learns whether the decision worked.
That is what it means for data to become part of how an organization operates.
The real opportunity for African businesses
Africa does not need businesses that merely collect more data.
It needs businesses that can make better use of the information they already generate.
The World Bank's research describes data as an input into production that can help firms improve decisions, reduce transaction costs, innovate and increase productivity. But it also emphasizes the infrastructure, institutions, skills and governance required for data to create value.
That is an important distinction for organizations deciding where to invest.
The next step may not be artificial intelligence.
It may not be a larger data warehouse.
It may not even be another dashboard.
It may be fixing the way customer information is captured.
It may be agreeing on what "revenue" means.
It may be connecting two systems that have been operating independently for years.
It may be replacing a monthly manual report with a process that updates every morning.
Or it may be discovering that the organization has been collecting information for years without ever deciding what questions that information was supposed to answer.
The real competitive advantage comes from the organizational capability built around data.
The businesses that win will increasingly be those that can answer questions faster, understand their customers better, detect problems earlier, allocate resources more intelligently and learn from their own operations.
In other words, the advantage will not belong merely to organizations that have data.
It will belong to organizations that know what to do with it.
And that is the difference between a business that collects data and a truly data-driven organization.
What should your organization do next?
If your business already has multiple sources of data but still relies heavily on manual reporting, intuition or disconnected spreadsheets, the first step is not necessarily to buy another technology platform.
Start by mapping your critical decisions.
Understand the data behind them.
Identify where that data comes from.
Measure its quality.
Establish who owns it.
Then design the systems, analytics and reporting processes required to support better decisions.
That is how data becomes a business capability rather than simply another organizational asset.
At Wikrena, we believe African organizations should not merely collect more data. They should build systems that help them make better decisions with the data they already have.
That is where meaningful data transformation begins.
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