How a Consulting Firm Eliminated 40 Hours of Monthly Reporting Overhead

Manual distribution was absorbing senior analyst capacity. The fix wasn't more headcount - it was removing the bottleneck entirely.

At a Glance

For a mid-size management consulting firm with 230 active clients, reporting was meant to be a key advantage. Clients were paying for clear, data-driven insights. The firm had a strong Power BI setup. Data models were well built, dashboards looked clean, and the analytics team knew what they were doing.

However, every month, senior analysts had to run the same manual process again and again. They pulled the reports for each client, applied the right client filters, exported the files, checked access permissions, sent the reports to the correct contacts, and logged that the reports were delivered.

It involved 11 analysts and 230 clients. By the time the process was finished, the team had spent more than forty hours every month just preparing and sending reports - before they could even start a real conversation about insights with clients.

Onboarding a new client made things even harder. Setting up their reporting, giving the right access, and checking the first report delivery usually took three to five business days for each client. With 20 to 30 new clients every quarter, the team was always trying to catch up.

Leadership thought about hiring more people. But the numbers did not make sense. If they added more analysts to fix the problem, the workload would just grow as the business grew. The real issue was not staffing - the delivery process itself was broken.

The main issue was not effort - the analysts were already working efficiently. The real problem was that Power BI lacked a built-in way to deliver reports to external clients - everything the firm needed to send clients' insights had to be handled outside the platform.

• No multi-tenant separation: Client data existed in shared workspaces. Segmentation was managed manually at export time - a governance risk on top of an efficiency problem.
• No automated distribution: Every report required human action to reach a client. There was no trigger, no schedule, no orchestration. Just analysts and export buttons.
• No self-service client access: Clients couldn't log in to see their own dashboards. They received files. Files got stale. Clients emailed asking for updates.
• No onboarding infrastructure: Each new client was a manual setup project - workspace creation, RLS configuration, contact verification, format decisions - handled differently every time by whoever picked it up.

The Head of Client Delivery and the Analytics Director evaluated three paths before selecting Reporting Hub:

• Build internally: The technology team scoped a custom multi-tenant delivery layer built on top of their existing Power BI environment. Estimate: 8–12 months, two to three FTEs, $150K–$250K before first delivery. Ongoing maintenance not included.
• Expand Power BI Service licensing: Giving clients direct Power BI access via Pro licensing was modeled at $14/user/month. With 1,800+ contacts across 230 accounts, the annual licensing cost exceeded $300K - before any orchestration or governance was built.
• Reporting Hub: An orchestration layer that sits on top of their existing Power BI environment, which handles multi-tenant delivery infrastructure natively, and deploys in 30 days without re-platforming their analytics stack.

The firm deployed Reporting Hub on the Growth tier. Implementation took 28 days from kickoff to the first automated delivery, against an internal build estimate of 8–12 months for equivalent capability.

The deployment covered three core workstreams:

During the deployment, BI Genius was activated at the Foundation tier. At first, it was used internally: the system generated AI-generated summaries for each client report, and the analytics team reviewed them through an approval workflow before anything was shared.

Once approved, the summaries were sent out along with the regular report set for a small group of clients as part of a pilot program.

The 40-hour monthly distribution cycle dropped to about 6 hours, and most of that time was spent reviewing configurations and handling occasional exceptions. Within the first month, senior analysts who had been stuck in export-and-send routines were able to shift their time back to client advisory work.

Client onboarding also improved. What used to take 3 to 5 business days now happens the same day. New accounts were set up through a standard workflow, so analysts no longer had to handle infrastructure setup themselves.

The financial impact was clear as well. The firm had been spending about $36,000 per year on report delivery work, based on 40 hours a month at $75 per hour. After the change, that cost dropped to roughly $5,400 per year, creating an annual recovery of $30,600, which more than covered the Reporting Hub Growth subscription.

Ninety days in, the operational improvements were clear. But another discussion began to grow at the same time—one that the firm had not expected when it first started looking at the platform.

With delivery now automated and client portals running smoothly, the analytics team finally had the time to think about something different. Instead of worrying about how to send reports, they could focus on how the client intelligence experience itself could improve.

From that shift in thinking, two outcomes began to take shape:

The firm's original goal had been simple: remove the manual work involved in delivering reports. What they discovered afterward was something bigger- Reporting Hub did not just make delivery more efficient - it changed what the firm could offer to clients.

Three factors drove the outcome: