Business intelligence uses records of business activity to help people understand performance and decide what to do. It combines shared measures with reports and follow-up analysis. Start with a recurring decision and implement the data, reporting and support it needs, so the recipient can inspect a change and use the result.
A manager sees that late deliveries increased last week. The first question is whether performance worsened or the company simply handled more orders. Answering it requires the right counts, comparable periods and a definition of what counts as late.
The chart is the beginning of that investigation. Its data and definitions let the manager determine what the movement means for the operation.
Data for a recurring decision
A useful BI system connects a recurring decision to the records that can inform it. Staffing and carrier decisions may depend on a delivery review; hiring plans may use a workforce review. In each case, the intended decision determines which measures are useful and when they need to update.
Source systems record activity for their own purposes. Their records may need to be joined, cleaned and organized before they can answer a question across departments. A shipment record, for example, may need the order's promised date before it can support a timeliness measure.
The reporting process should retain enough detail to investigate its totals. If a number is challenged, the team needs to identify the relevant records and calculation. This makes BI useful beyond presentation: the same foundation can support a recurring report and the questions that follow it.
Shared measures across the business
People need the same definition when they compare the same business measure. Specify what is counted, which period applies and which records are excluded. Give the definition an owner who can resolve a question about its meaning.
A measure called “new customers” might count signed agreements, first orders or first completed deliveries. Each can be valid for a different purpose. Naming and documenting the distinction lets people use the right measure without treating every disagreement as a data error.
Keep the required history in the model. A customer's current segment can differ from the segment assigned last year, changing the apparent trend. Decide whether the report needs the historical classification or a restated view of today's organization, then apply that choice consistently.
Reports and follow-up analysis
Reporting makes a change visible; analysis investigates what the change means. A weekly scorecard can show delivery performance by location. Follow-up analysis can examine whether the movement is concentrated in a carrier, product group or particular day.
The investigation should retain the report's period and population until there is a reason to change them. Otherwise, a plausible explanation may describe a different set of orders. Show any new comparison clearly, along with the evidence that supports it.
A forecast estimates what may happen under stated assumptions. Put those assumptions beside the result and distinguish the estimate from recorded historical activity. Both can inform the same decision, but the reader needs to know which kind of evidence each supplies.
Choosing the reporting experience
Choose the experience around how the recipient uses information. A meeting may need a scheduled document. Someone investigating a movement may need to filter a period in an interactive view or ask a follow-up question in plain English. Test the experience that matches the actual task.
Evaluate those experiences with a familiar task. The recipient should be able to find the measure, understand its period and follow the evidence behind it. Check the result with the permissions that person will actually have, including access when the report is shared.
Useful existing models and reports can remain part of the solution. When the difficulty lies in disconnected sources or disputed definitions, include those in the implementation scope. The BI tools guide describes different ways to combine that data work with a reporting experience.
The people behind the system
Software and delivery responsibilities need to be chosen together. A first data hire can learn the business and establish priorities, but the role also needs capacity to deliver. Include connections, modeling, reporting and operation when deciding what that person will own and where implementation support would help.
An implementation team can take on those delivery tasks and help the organization introduce the result into everyday work. The business retains decisions about priorities and what its measures mean. The arrangement should make it clear who resolves a failed refresh or changes a calculation when the process evolves.
Databasin implements its data and AI platform around the business result, including source connections, shared measures, Data Apps and automated workflows. The team also handles rollout and training. Continuing support can cover the work the organization needs help operating and improving.
Measuring whether BI helps
Judge BI by the work completed after someone sees the result. A report that people open frequently may still leave them exporting data and rebuilding the calculation. Observe the task from the first question to the decision, including the checks and corrections in between.
A useful pilot can establish a baseline for that effort and identify the recurring delays. After rollout, review whether people can complete the task with less manual assembly and whether they understand the measures. Training and feedback help distinguish a data problem from an unfamiliar way of working.
Include operation in the implementation decision. The workload and available expertise determine how much managed operation or continuing support is useful. Agree which work stays inside the organization and which work the delivery partner will maintain, in relation to the result people need.
Example: investigating late deliveries
This illustrative weekly review checks whether more late orders indicate a decline in delivery performance.
| Check | Previous week | Current week | Meaning for the review |
|---|---|---|---|
| Delivered orders | 1,000 | 1,200 | The population increased by 200 orders. |
| Late orders | 50 | 60 | The count increased by 10 orders. |
| Late-delivery rate | 5% | 5% | The overall proportion remained unchanged. |
| Next investigation | Same lateness definition | Same lateness definition | Examine locations and carriers for changes hidden by the overall rate. |
The late-order count rose because the total population grew at the same rate. The manager can now investigate individual locations and carriers for a change that the overall percentage might conceal.
Start with one business decision
- Identify the recipientIdentify who makes the recurring decision and what they do with the result. Establish which information would change the action they take.
- Define the measureRecord its calculation, period, population and exclusions. Resolve different meanings before putting the same label on several reports.
- Test the whole taskFollow the recipient from the question through the report to its evidence. Include sharing, refresh timing and a disputed figure.
- Arrange ongoing ownershipEstablish who maintains sources, changes definitions and supports users. Review the completed business task after rollout to choose further improvements.
Discuss business intelligence in practice
We can discuss the questions people need to answer and where reporting becomes difficult to use. Our team can explore the data, definitions and delivery work involved in making those answers part of everyday decisions.