Business Intelligence with AI
The problem is rarely that you need more reports.
What is business intelligence?
Business intelligence means being able to answer questions about your own business reliably, which depends far more on agreed definitions and trusted figures than on the reporting technology used to display them.
Organisations that describe themselves as needing business intelligence usually already have reporting. What they lack is agreement about what the numbers mean and confidence that they are right.
Adding another reporting layer on top of that produces a fourth version of a disputed figure, delivered faster. The meetings still open by arguing about whose number is correct.
The order that works is unglamorous: agree definitions, establish that figures can be traced, then decide what to display. Almost every failed BI project got that order backwards.
Why we do not start with a platform
Duara works on business intelligence in Kenya starting from definitions and trust rather than from tooling.
We will not begin with a platform selection. The question of which BI tool to buy is the one clients want to start with and the one that matters least, and answering it first is how organisations end up with an expensive system nobody believes.
Who this is for
- Departments quote different figures
- Reports exist and are not trusted
- Meetings argue about numbers rather than decisions
- Somebody has proposed buying a BI platform
Industries we serve
- Manufacturing groups
- Distribution and retail
- Financial services
- Healthcare groups
- Logistics
- Large professional services
Problems this solves
These are trust and definition failures, which no amount of additional reporting resolves.
- Figures that disagree. Two departments produce different numbers for the same measure, and both are defensible under their own definition.
- Reports nobody trusts. Reporting exists and decisions are made on instinct anyway, because nobody is confident the numbers are right.
- Meetings spent on the data. Time that should be spent deciding is spent establishing whose figure is correct.
- Tooling chosen first. A platform is selected before definitions are agreed, which produces a faster version of the same disagreement.
What we deliver
Definitions agreed and written down, figures made traceable to source, trust established before any display layer, and reporting built only on measures people accept.
Agreed written definitions for core measures
Every figure traceable to its source records
Reconciliation between existing conflicting reports
Reporting built only on trusted measures
A view on whether a new platform is needed at all
Documentation your team owns
Features
- Definitions before tooling. The platform question matters least and clients want to start with it, which is how organisations buy systems nobody believes.
- Traceability as the trust mechanism. A figure you can follow to source is trusted. One you cannot is argued about regardless of how well it is presented.
- Existing conflicts reconciled. Where two reports disagree we establish why, which usually resolves more than any new report would.
- Nothing displayed until it is trusted. Publishing a disputed measure faster spreads the dispute rather than settling it.
- Honest view on new platforms. Frequently your existing tools are adequate and the problem was never the technology.
Benefits
- Meetings discuss decisions. Agreed definitions remove the argument that opens most management meetings.
- Reporting gets used. Figures people trust get acted on, which is the only thing that makes reporting worth producing.
- Money not spent on tooling. Establishing that your current tools are adequate is frequently the most valuable outcome.
- Disagreements resolved once. A definitional conflict settled properly does not resurface every quarter.
Technologies we use
- Definition workshops. Establishing what each core measure means, with the departments that use it.
- Traceability. Ensuring any figure can be followed back to the records behind it.
- Reconciliation. Explaining why existing reports disagree, which is usually definitional rather than technical.
- Source connection. Reading from operational systems rather than from exports somebody maintains.
- Display design. Building reporting on measures that have been agreed, which comes last rather than first.
The failure mode is universal and structural. Reporting technology is easy to buy and definitional agreement is difficult to reach, so organisations do the easy part first and wonder why nothing improved.
How the process works, step by step
BI work usually takes six to twelve weeks, and roughly half of it happens before anything is displayed.
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Step 1
Free reporting review
We look at what reporting exists, whether it is trusted and where figures currently disagree.
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Step 2
The platform question answered
We say whether you need a new tool, and frequently the answer is that your existing one is adequate.
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Step 3
Definitions agreed
Core measures are defined with the departments that use them, which is where the real disagreements surface.
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Step 4
Traceability established
Figures are made followable to source, since that is what converts a number into something people accept.
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Step 5
Reporting built
Display comes last, on measures that have been agreed and can be traced.
Quality assurance and how we work
The commitments attached to producing the numbers an organisation runs on.
- We do not start with platform selection. It is the question clients want first and the one that matters least, and answering it first produces a system nobody believes.
- Nothing is displayed until it is trusted. Publishing a disputed figure faster spreads the disagreement rather than settling it.
- We explain why existing reports disagree. The reconciliation is frequently more valuable than anything new we build.
- We say when your current tools are adequate. Establishing that no new platform is needed is a legitimate and common outcome, and it costs us the larger project.
- Definitions are documented and yours. They are written down and handed over, because a definition only we hold recreates the dependency.
Frequently asked questions about business intelligence
Do we need a BI platform?
Frequently not. It is the question clients want to start with and the one that matters least, and your existing tools are often adequate.
Why do BI projects fail?
On definitions and trust rather than technology. Organisations do the easy part first, which is buying a tool, and wonder why nothing improved.
Our departments produce different numbers, why?
Usually because each has a defensible definition of what counts. That is a definitional problem and no reporting layer resolves it.
Would faster reporting help?
It would produce a disputed figure faster. The meeting still opens with an argument about whose number is right.
What comes first then?
Agreed definitions, then traceability, then display. Almost every failed project got that order backwards.
Why does traceability matter so much?
Because a figure you can follow to source is trusted, and one you cannot is argued about regardless of how well it is presented.
Can you reconcile our existing reports?
Yes, and explaining why they differ is frequently more valuable than anything new we would build.
How long does BI work take?
Six to twelve weeks, and roughly half of that happens before anything is displayed.
Will you tell us not to buy a platform?
Yes, when that is the honest answer, and it costs us the larger project. Your current tools are adequate more often than suppliers admit.
What does the AI part actually do here?
Plain language explanation of what changed and anomaly surfacing. The definitional work is human and it is the part that decides success.
Can we display a measure people dispute?
We advise against it. Publishing a disputed figure faster spreads the disagreement rather than settling it.
Who should agree the definitions?
The departments that use each measure, together. Definitions agreed by one function get rejected by the others.
What if departments cannot agree?
Then somebody has to decide, and that is a management call rather than a technical one. We surface it rather than choosing quietly.
Does it connect to our source systems?
Yes, reading from operational systems rather than from exports somebody maintains by hand.
Can it work with our existing dashboards?
Yes, and building on what you have is usually cheaper and better adopted than replacing it.
How do we keep definitions current?
They are documented and yours to maintain. A definition only we hold recreates the dependency we removed.
Will this improve decisions?
It removes the argument about the data. Whether better decisions follow is management work rather than something we can supply.
Is this the same as dashboards?
Dashboards are the display layer, which comes last. This is the definitional and trust work that has to happen first.
Who can see the reporting?
Whoever you authorise, following your existing access rules rather than opening figures more widely than intended.
What does BI work cost?
Measure count and source complexity determine it, quoted after the reporting review.
Glossary of terms
Business intelligence terms in plain language.
- Measure definition
- The agreed rule for what a figure counts and when, which is where most BI projects actually fail.
- Traceability
- Being able to follow a reported figure back to the records behind it.
- Reconciliation
- Explaining why two reports of the same thing differ.
- Source system
- Where data originates, as opposed to an export somebody maintains manually.
- Single version of truth
- One agreed figure per measure, which requires definitional agreement rather than software.
- Display layer
- The dashboards and reports people see, which should be built last.
Related services in AI Solutions
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Ask your finance and operations leads for last month revenue. If the figures differ, no platform will fix that.
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