FeaturedAnalytics & BI3 min read
GGMS Insights
Ideas built for decisions,not display.
Practical guides to data modelling, reporting, and automation. Explore implementation checks, technical references, and clearly attributed stories from other organizations.
Explore the libraryFrom the briefing desk
Questions behind the next decision.
A focused reading list for leaders shaping performance, operations, customer experience, and data foundations—not a catalogue of technology trends.
Source references for technical contextPractical guides for active initiativesArchitecture perspectives connecting technology and decisions
Published external case studies
What organizations have put into practice
These are Microsoft-published customer stories, not GGMS projects or client endorsements. Summaries describe the publisher’s account; the lessons are our interpretation. Follow the source for its full context.
Kraft Heinz
Giving sales teams a shared reporting foundation
Microsoft describes Kraft Heinz working with Microsoft and EY to move legacy reporting to Power BI on Azure. The story connects platform work with the sales team's need to identify opportunities across retail customers.
Our reading: start with the sales review and the customer hierarchy before choosing dashboard layouts.
Read the Microsoft story about Kraft HeinzNHS Property Services
Connecting cleaning audits to operational reporting
Microsoft's customer story describes a Power Platform cleaning-audit application that schedules audits and sends submitted results into Power BI dashboards and reports.
Our reading: capturing a structured event at the point of work can be as important as the report built on top of it.
Read the Microsoft story about NHS Property ServicesMarks & Spencer
Making a shared data platform usable across retail
Microsoft describes M&S using Azure Synapse Analytics and Power BI, with its BEAM team opening access to relevant data across the business and automating pipelines and reports.
Our reading: a shared platform needs an ownership and access model as well as data movement.
Read the Microsoft story about Marks & SpencerBrowse the library
Latest perspectives
11 articles across all topics
Practical guideAnalytics & BI3 min read
Social media analytics: reach, response, and measurement gaps
Connect content, audience, campaign, engagement, and conversion signals so teams can understand what changed and decide what to do next.
September 2026Read insight
Architecture perspectiveAnalytics & BI3 min read
E-commerce analytics: reconcile orders, refunds, and margin
A dependable commerce model follows the customer and order journey from demand creation through payment, delivery, returns, and contribution.
September 2026Read insight
Practical guideAnalytics & BI2 min read
Marketing measurement: what evidence should change the budget?
Align objectives, spend, audiences, campaigns, journeys, and commercial outcomes before selecting a more sophisticated measurement method.
September 2026Read insight
Architecture perspectiveAnalytics & BI3 min read
Finance reporting from SAP to Power BI: a reconciliation checklist
Finance reporting becomes dependable when definitions, controls, data grain, and ownership are designed before the executive dashboard.
September 2026Read insight
Practical guideIndustry Intelligence3 min read
Supply chain visibility: track the promise, shipment, and receipt
Connect assets, materials, manufacturing, inventory, and logistics around shared events, decisions, and exceptions.
September 2026Read insight
Practical guideIndustry Intelligence3 min read
Distributor analytics: reconcile stock and secondary sales
Move beyond sales totals to understand territory execution, product movement, inventory exposure, and channel action.
September 2026Read insight
Practical guideIndustry Intelligence3 min read
Airline sales analytics: compare bookings at the same horizon
A commercial model should connect route, market, channel, booking behavior, and sales activity without losing time context.
September 2026Read insight
Architecture perspectiveData Engineering3 min read
Data pipelines for AI: replay, reconcile, and validate
Why AI-ready data depends on observable pipelines, stable definitions, quality controls, and ownership—not model choice alone.
September 2026Read insight
Practical guideAI & Automation2 min read
AI in reporting: automate the draft, keep the evidence
Use AI to reduce repetitive work, surface context, and coordinate action—while preserving review where judgment matters.
September 2026Read insight
Practical guideIndustry Intelligence2 min read
Workforce analytics: define headcount before comparing teams
Organize headcount, movement, recruitment, attendance, and structure around workforce decisions—not isolated HR extracts.
September 2026Read insight
Practical guideIndustry Intelligence2 min read
Healthcare operations: measure staffed capacity and service flow
Connect demand, service flow, workforce, and capacity using governed measures that support operational coordination.
September 2026Read insight
Strong insight makes a complex decision easier to understand, challenge, and act upon.
Our editorial standard
Useful before impressive.
Each guide explains a specific decision, the data needed to support it, and checks to run before release. External case studies name their publisher. GGMS client stories require approved project facts and permission to publish.
Traceable sources
Technical references are linked so readers can check the underlying concepts.
Decision-centered
Organized around the choices, controls, and operating response—not a software feature list.
Technology-aware
Platforms are discussed only where they materially change architecture, delivery, or governance.
Clear attribution
Public customer stories are labelled as external examples. Proposed approaches are not presented as delivered results.
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Bring us the decision, workflow, or data problem behind it.
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