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AI and automation

Data and reporting systems

Create one reliable view of the information your organization uses to make decisions.

Good-fit situations

  • Two reports answer the same question differently.
  • Staff maintain private spreadsheets because they do not trust the shared dashboard.
  • Monthly reporting takes days of manual work.
  • The necessary data exists but is spread across several systems.
  • Key terms such as customer, active account, order, or completion have no shared definition.

What you receive

  • Agreed definitions and ownership for key measures
  • A map of source systems and data quality issues
  • Integration and reconciliation rules
  • A reporting model centered on actual decisions
  • Dashboards or recurring reports with documented logic
  • A process for investigating and correcting discrepancies

Process

How the work proceeds

  1. Agree the definitions first

    Most reporting disputes are definition disputes wearing a technical costume. Settle what counts as a customer before designing the report.

  2. Identify the authoritative source

    For each field, one system is the record of truth and the others defer to it.

  3. Reconcile and integrate

    Bring the data together with the reconciliation rules written down rather than held in someone's head.

  4. Report on decisions

    Build the smallest reporting set that changes a decision or an action.

Selected example

Customer-record reconciliation

Situation.
Duplicate and incomplete customer records had accumulated in a CRM, so reporting built on that data could not be trusted.
Work.
Built a recurring workflow that identifies duplicate and incomplete records using agreed business rules and routes them for review.

Related

The rest of the practice

Explore the full AI and automation practice

Start with the specifics.

Describe the task, the systems involved, and who is responsible for it today. That is enough for a first conversation.