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Scenario 02 Professional Services

Analytics transformation at scale.

Meridian Advisory Group

  • RoleDirector of Data & Analytics: Transformation & Delivery
  • IndustryProfessional Services
  • Scale800 employees, four practice areas
  • Timeline9 months: assessment to BI platform deployment

Meridian Advisory Group is a fictitious organization. This scenario is a composite drawn from patterns commonly observed in professional services firms managing analytics at scale. It is included here to illustrate strategic thinking and leadership approach.

Section 01

About Meridian Advisory Group

Meridian Advisory Group had built a strong reputation over 20 years advising mid-market companies through growth and transformation. Their consultants were sharp. Their client relationships were strong. But internally, the firm was running on spreadsheets.

Every practice area had its own reporting process. Weekly performance updates were assembled manually by analysts who spent most of their time pulling numbers from disconnected systems rather than interpreting them. By the time leadership received a report, it was already three days old and formatted differently from the one before it.

The firm had grown quickly through a series of acquisitions, which made the data problem worse. Each acquired entity brought its own tools, its own definitions, and its own way of measuring success. Nobody agreed on what a billable hour meant across practices.

Leadership Landscape

Managing Partner
22-year firm veteran focused on client growth and market reputation. Skeptical of internal technology investments.
COO
Operationally sharp, frustrated by the lack of reliable data to manage capacity and utilization across the firm.
CFO
Wanted faster financial close cycles and better visibility into project profitability. Had already flagged reporting inconsistency as a risk in the last board review.
Section 02

The Situation

The firm's data environment had not kept pace with its growth. There were over 120 active reports across the four practice areas. Most were built by individual analysts in Excel, emailed as attachments on a weekly cycle, and rebuilt from scratch whenever someone left the team.

Leadership was making resourcing decisions without reliable utilization data. The CFO was closing the books manually each month using a process that involved reconciling seven different spreadsheets. Project profitability was tracked inconsistently, and in some practice areas, not tracked at all.

A trigger came when the firm lost a competitive pitch. The prospective client had asked for evidence of Meridian's internal operational maturity. The answer was thin. The Managing Partner decided it was time to fix the foundation.

Section 03

The Diagnosis

The first three weeks involved a structured assessment: interviews with practice leads and analysts, a full inventory of existing reports, and a review of the underlying data sources feeding them.

Four problems stood out.

1. Report sprawl without ownership. Of the 120+ reports in circulation, fewer than 30 were being actively used by decision-makers. The rest existed because someone had once asked for them and nobody had turned them off. Analysts were maintaining reports that leadership had stopped reading months ago.

2. No single source of truth. The same metric, revenue per consultant, was calculated four different ways across four practices. Leadership debates were regularly derailed by disagreements about whose numbers were right, rather than what the numbers meant.

3. Data work was analyst work. Senior analysts were spending an average of 60% of their time on data preparation and report formatting. That left 40% for actual analysis. The ratio was backwards and the firm was paying consulting-rate salaries for spreadsheet maintenance.

4. No infrastructure for scale. The firm had a CRM, a project management system, and a finance platform, none of which talked to each other. Any cross-functional view of the business required a manual extraction and merge process that took two days minimum.

Section 04

The Strategic Response

Establishing the Direction

The case was made to leadership early: this was not a reporting project. It was a decision infrastructure project. The goal was not to produce prettier reports. It was to give leadership the information they needed, when they needed it, in a form they could act on.

Three outcomes were committed to at the outset:

  • Analysts would spend less than 20% of their time on data preparation within 9 months
  • Leadership would have access to a single, trusted view of firm performance updated daily
  • Financial close time would be cut by at least 40%

Reducing Before Building

The first move was consolidation, not construction. Before any new platform was built, the 120+ report inventory was reviewed and rationalized with each practice lead. Reports were classified into three categories: keep and migrate, consolidate with others, or retire.

Sixty-two reports were retired in the first 30 days. This was not a technical decision. It was a change management conversation with each practice, walking through what decisions each report was supposed to support and whether it actually did.

Getting to 58 reports before building anything meant the platform would reflect what the business actually needed, rather than inheriting years of accumulated requests.

Platform Architecture

The recommendation was a three-layer architecture:

Data integration layer
Connect the CRM, project management system, and finance platform through a centralized pipeline, standardizing field definitions and establishing agreed metric logic before anything reached a dashboard
Semantic layer
A governed business logic layer where metrics like revenue per consultant, utilization rate, and project margin were defined once and applied consistently across all reports and all practices
Presentation layer
Power BI dashboards built to serve three distinct audiences: executive leadership (firm-wide performance), practice leads (team utilization and pipeline), and project managers (individual project health)

Metric definitions were documented, reviewed with the CFO's team, and signed off before development began. The semantic layer meant that when the COO and the CFO looked at utilization numbers, they were looking at the same calculation.

Governance From the Start

A data governance working group was formed with representation from each practice area. This group owned three things: approving new metric definitions, reviewing data quality issues flagged by the platform, and managing requests for new reports through a structured intake process.

The intake process was deliberate. Any new report request required a description of the decision it would support and who would act on it. This stopped the sprawl from rebuilding itself.

Section 05

Execution Plan

Months 1 and 2: Assessment and Consolidation

  • Complete report inventory and usage audit across all four practices
  • Facilitate practice-by-practice rationalization sessions; retire 60+ inactive reports
  • Map all data sources and document current metric definitions
  • Stand up data integration pipelines connecting CRM, project management, and finance systems
  • Form data governance working group; establish intake process for new report requests

Months 3 and 5: Build

  • Develop and validate semantic layer with agreed metric definitions, signed off by CFO and COO
  • Build executive dashboard covering firm-wide revenue, utilization, headcount, and project margin
  • Build practice-level dashboards for each of the four areas
  • Run structured feedback sessions with each practice lead; iterate before release

Months 6 and 7: Rollout and Adoption

  • Phased rollout by practice area, starting with finance and operations
  • Analyst training sessions focused on self-serve reporting within the platform
  • Retire the weekly Excel-based reporting cycle; transition leadership to live dashboards
  • Establish a monthly data quality review process within the governance working group

Months 8 and 9: Optimization and Handoff

  • Review platform performance against the three committed outcomes
  • Identify Phase 2 opportunities: project forecasting, pipeline analytics, client profitability modelling
  • Document platform architecture, governance model, and operating procedures
  • Transition day-to-day ownership to the analytics lead and governance working group
Section 06

Business Impact Targets

MetricTarget
Reports retired or consolidated60+ within first 30 days
Analyst time spent on data preparationReduced from 60% to under 20%
Financial close cycle reduction40% faster
Leadership dashboards available daily vs. weeklyYes
Single agreed definition for all firm-wide metricsAchieved before platform launch
Phase 2 analytics roadmap deliveredMonth 9
Outcome

What this delivered.

The first visible win came early. Retiring 62 reports in the first month sent a clear signal that this initiative was different from the technology projects the firm had attempted before. Practice leads had been waiting for someone to give them permission to stop maintaining reports nobody used.

By month five, the COO had daily visibility into utilization rates across all four practices for the first time in the firm's history. Resourcing conversations shifted from arguments about whose spreadsheet was correct to actual decisions about where to deploy capacity.

The CFO closed the books three weeks into month seven using the platform for the first time, with no manual reconciliation step. That had never happened before.

The analysts who had spent most of their weeks on report preparation were redirected to client-facing analytical work. Several practice leads noted that the quality of internal analysis improved noticeably once analysts had time to actually do it.

Meridian went into the following fiscal year with a data foundation that matched the firm's external reputation. The Managing Partner included the analytics transformation in the next client pitch. This time, the answer to the operational maturity question was concrete.

Meridian Advisory Group is a fictitious organization. This scenario is a composite drawn from patterns commonly observed in professional services firms managing analytics at scale. It is included here to illustrate strategic thinking and leadership approach.