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Manka

One disbursal number finance and sales agree on

Your LMS, CRM, accounts and spreadsheets in one clean store, with the few dashboards you check every Monday.

Everything a good analytics project should include

  • Data pipelines

    Scheduled pulls into one store, checked for gaps.

  • Leadership dashboards

    Disbursals, collections and sales on one screen.

  • Automated MIS

    The reports you build by hand, sent on schedule.

  • Portfolio analytics

    DPD buckets, roll rates and vintage curves.

  • Statement analytics

    ABB and bounces from bank statements, using our BSA.

  • One definition per KPI

    Every number traced back to its source.

Why nobody trusts the Monday numbers

  • Problem: Every department has its own number for the same KPI

    What we build: One definition per metric, computed once.

  • Problem: Your MIS is a 40-tab Excel only one person understands

    What we build: Pipelines rebuild it every morning.

  • Problem: You learn about rising delinquency at month-end

    What we build: Daily bucket movement and early alerts by branch.

  • Problem: Underwriters read statements line by line

    What we build: BSA turns the PDF into a one-page summary.

A plan with dates, not a black box

  1. 01

    KPI workshop

    The decisions you make and the numbers behind them.

  2. 02

    Data audit

    Sources, quality checks and agreed definitions.

  3. 03

    Pipelines and storage

    Scheduled, cleaned and fast to query.

  4. 04

    Dashboards and MIS

    Built in rounds with the people who use them.

  5. 05

    Iteration

    New metrics as the business asks for them.

Questions

Do we need a data warehouse?

Not always. One or two databases can run on a read replica. Several systems need a small warehouse.

Which dashboard tool do you use?

Usually Metabase or Superset, with no per-user fees. We can use your BI tool instead.

Can you work with data still in Excel?

Yes. A fixed template and an upload point, checked and loaded automatically.

How do you keep customer data safe?

Read-only access, and personal data masked outside production.

Planning your analytics project?