Customer Story

ThoughtSpot Brings AI-Powered Self-Service Analytics to Five Business Units within Org

What we did

Rolled out ThoughtSpot across five business units to put AI-powered self-service analytics in the hands of commercial users.

Delivered 10+ analytics use cases, including a reusable Muze charting framework that reduced setup time for KPI cards by roughly 1-2 hours per card.

Embedded enablement throughout the engagement so the client’s team is independently extending liveboards, search-driven analytics, and Spotter-powered AI insights as the platform scales.

Industry

  • Healthcare

Technologies

  • ThoughtSpot

ThoughtSpot in Production Across

5 BUs (and growing)

ThoughtSpot supports day-to-day decision-making across diverse business functions at a global HLS enterprise.

10+ Analytics Uses

Cases Delivered

Client has a growing portfolio of use cases across market performance, product usage, distribution, and plan-vs-actual analysis.

~50 Users Enabled

By Analytics8

Hands-on training and working sessions helped users build confidence with liveboards, Search, and Spotter-powered insights

The Challenge

This global biopharma company needed to support a growing number of analytics requests across commercial business units and product lines. Teams needed answers about market share, product performance, retailer activity, distribution, coverage, and patient experience, but the existing static reporting model could not keep pace.

New questions often required another report, dashboard update, or analyst pull, slowing decision-making and limiting business users’ ability to explore data independently. The company also needed to support both business users seeking quick, self-service insights and more advanced users requiring deeper analytical flexibility.

To modernize analytics across the organization, the company selected ThoughtSpot and partnered with Analytics8 for implementation, delivery, and enablement support.

The Solution

Analytics8 brought in a team of experts, working alongside the client’s IT and analytics teams on a shared delivery roadmap. The work prioritized enablement throughout: rather than building solutions for the client, the focus was on guiding and supporting the team as they developed their own analytics capabilities within ThoughtSpot, through hands-on training, dedicated workstreams, and real-time resolution of platform-specific roadblocks.

The project entailed:

  • Standing up dedicated workstreams to design and deliver 10+ AI-powered BI use cases across five commercial business units, focused on retailer and market performance, product usage, and distribution analytics
  • Architecting ThoughtSpot-optimized data models with row-level and role-level security so each business group sees only the data it should
  • Creating governed semantic data models that support consistent KPI definitions, reliable results, and “last-mile” business logic inside ThoughtSpot.
  • Re-architecting and remapping a confidential business function’s master data model to align with business needs and support governed access directly within ThoughtSpot
  • Building a reusable Muze chart framework for plan-vs-actual comparisons that standardizes visualization patterns and saves roughly 1–2 hours per KPI card where the framework is used
  • Creating website-style interactive dashboards that let users navigate, drill, and explore data in an intuitive, app-like experience rather than a traditional dashboard layout
  • Enabling Spotter so business users can ask questions in plain language, translate business terms into governed analysis, and get answers without writing queries or waiting for a new dashboard build.
  • Running hands-on training, cross-team working sessions, and real-time roadblock resolution with the client’s analytics teams

Business Impact

ThoughtSpot is now part of how commercial teams work with data. Across five business units, users can access liveboards, explore governed data, and ask follow-up questions through Search and Spotter instead of relying on static exports, PowerPoint decks, printed Excel reports, or packaged reporting handoffs.

Analytics8 directly enabled ~ 50 users, supported 10+ analytics use cases, and helped multiple teams reach the point where they can build and deploy some ThoughtSpot use cases on their own.

The business impact shows up in three ways:

  • Faster access to business answers: Commercial teams can use liveboards and Spotter directly in meetings and working sessions, asking questions in business language and getting answers in minutes instead of waiting weeks for a new report or dashboard iteration.
  • A more scalable analytics delivery model: The client is no longer treating every new question as a one-off dashboard request. Natural language search, reusable dashboard patterns, and the Muze framework help teams explore new questions faster while saving roughly 1-2 hours per KPI card where the framework is used.
  • Reliable self-service at scale: Governed semantic models, customized KPI definitions, and row-level security give users flexibility to explore data while keeping results consistent, secure, and grounded in approved business logic.

The result is a shift from static reporting to governed, AI-powered self-service analytics. Business users can ask questions in their own language, data professionals can move faster without rebuilding dashboards for every request, and internal analytics teams can keep scaling ThoughtSpot across future use cases with more control and consistency.

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