Analytics Modernization · SAP Datasphere · SAC on BTP
How Johnson Health Tech replaced a failed SAP BW with Datasphere and SAC in three waves
Delivered 2026
After a critical SAP BW failure left Finance fielding requests across the business, Mindset built a ground-up Datasphere and SAC platform for Johnson Health Tech, delivering 10+ production models across Finance, Sales, and Supply Chain and getting the first self-service wave live in under two months.
By the numbers
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10+
Production data models across Finance, Sales, and Supply Chain
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<2 mo
From dev start to first self-service wave
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3 waves
Phased delivery covering 2 complete, 1 in progress
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2026
S/4HANA-ready architecture surviving the planned upgrade
Before
A failed BW and a Finance team fielding everyone's reports
- Legacy SAP BW controlled by the Taiwanese parent, slow to change and disconnected when they needed it most.
- Five financial analysts carrying the reporting load for NA, Canada, Mexico, and the wellness division with custom Z-reports and Excel.
- No self-service capability, and a planned S/4HANA upgrade that would require rebuilding whatever they replaced BW with.
After
A modern Datasphere and SAC platform, ready for S/4HANA
- 10+ production models covering Finance, Sales, and Supply Chain with self-service access across the business.
- Custom CDS views with real-time delta extraction, automated task chains, and currency and timezone issues resolved.
- Internal team trained and running independently, with architecture confirmed S/4HANA-ready for the 2026 upgrade.
“Business teams build a large amount of Excel-based reporting, expending a lot of time, and resulting in reports that are not always up to date.”
Built on
- CDS Views
- Task Chains
- Data Flows
- Cloud Connector
- Azure Entra / IAS
- SAP BW (legacy, retired)
Why this matters
A BW failure forced a faster reckoning with modern SAP analytics. Mindset built a platform that was already S/4HANA-ready before the upgrade started, so JHT got to skip the rebuild.
The challenge
In early 2025, Johnson Health Tech lost connectivity to its legacy SAP BW reporting platform. BW was controlled by the company's Taiwanese parent, which meant any field-level change was slow and centralized. When it failed, Finance became the de facto reporting engine for the North American business and several subsidiaries across Canada, Mexico, and the California wellness division.
Five financial analysts were carrying most of the reporting load with custom SAP reports and manual Excel workarounds that did not scale with the company's rapid growth. Business teams, in the words of JHT's own Corporate Controller, were "building a large amount of Excel-based reporting, expending a lot of time, and resulting in reports that are not always up to date."
JHT also had an S/4HANA upgrade planned for early 2026 and did not want to build something they would have to throw away. They needed a modern analytics platform that would survive the migration.
What we did
Mindset proposed SAP Datasphere and SAP Analytics Cloud before the S/4HANA upgrade, specifically because the work would carry forward onto the new ERP. The team built the platform from the ground up in three delivery waves.
Rather than relying on out-of-box extractors, Mindset built custom CDS views with composite timestamp logic for real-time delta extraction. The team also built automated task chains and data flows, and solved several hard technical problems along the way: Taiwan Dollar decimal conversion, timezone conversion from Taiwan (UTC+8) to each plant's local time, and a critical platform-level bug where date-partitioned remote tables silently dropped records.
Delivery included two on-site visits at JHT's North American headquarters (June and October 2025) and a strong knowledge-transfer focus. The client's internal analyst was trained on report building, and the team produced full handoff documentation so JHT owns the platform going forward. Azure Entra authentication migration completed in December 2025.
The outcomes
JHT got a working, modern analytics platform after the BW failure, with the first wave of self-service models live in under two months from development start. Ten-plus production data models reached delivery across Finance, Sales, and Supply Chain.
Users gained self-service access to GL, Journal Entry, COPA, GL hierarchy, Sales and Billing documents, pricing conditions, rebates, inventory stock with projections, open orders, delivery performance, and PO schedule lines. The need for Z-reports went down as the data layer got cleaner.
The October 2025 on-site was rated highly successful by the Mindset technical lead. JHT's internal team is now trained to extend the platform, and more business units have already asked to join. Because the architecture was built for S/4HANA readiness, the entire platform carries into the 2026 upgrade.
On stage & in the press
If we built this today
Concept · not delivered scopeBuilt on Business Data Cloud from day one.
This is a forward-looking concept, not the scope we delivered on this engagement. It is the build we would reach for now, grounded in SAP that ships today.
When Johnson Health Tech lost its parent-controlled SAP BW and Finance became the de facto reporting engine, the real need was governed self-service analytics the business could own, not another centralized stack waiting on someone else.
The Joule agent
Knowledge Graph Navigator
Reads the Finance, Sales, and Supply Chain models in SAP Datasphere through the SAP Knowledge Graph and answers business questions in plain language, drafting the SAC story or filter set instead of waiting on a custom Z-report. It proposes the view and a human confirms before it gets saved.
SAP Datasphere, SAP Analytics Cloud, FI, CO, SD, MM · PROPOSE · Self-service report turnaround (days from request to answer)
The Fiori app
SAP Analytics Cloud with embedded Joule
Joule sits inside SAC so analysts ask for a trend, a variance, or a breakdown in natural language and get a draft story grounded in the live Datasphere models. This is a real analytics surface, not a transactional Fiori app, so we name it honestly.
Joule embedded in SAP Analytics Cloud
The data product
Governed data product on SAP Business Data Cloud
A governed data product on SAP Business Data Cloud brings GL, billing, inventory, and order data together with shared semantics, so the agent and the dashboards read the same numbers without copying data out of the source. It is the modern home for the 10-plus models the team built by hand.
Data product on SAP Business Data Cloud
We would mine the existing reporting and request flows in SAP Signavio first, map the BW and Z-report landscape against the target models in SAP LeanIX, and let our MIND accelerators carry the old logic onto Datasphere and SAC so nothing gets lost in the move.
What we built
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Ground-up SAP Datasphere build
Complete data layer built from scratch using custom CDS views with composite timestamp logic for real-time delta extraction, automated task chains, and data flows.
10+ production data models across Finance, Sales, and Supply Chain
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SAP Analytics Cloud (SAC) reporting layer
SAC deployed as the self-service reporting front end for JHT's North American business and subsidiaries, replacing manual Excel workarounds.
First self-service wave delivered in under 2 months from dev start
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Finance models (GL, COPA, Journal Entry, FSV hierarchy)
Production models covering General Ledger, Journal Entry, COPA, and GL hierarchy via Financial Statement Version for Finance reporting.
Finance self-service live in Wave 1
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Sales and pricing models
Production models covering Sales and Billing documents, price book, pricing conditions, and rebates for the commercial team.
Sales self-service live in Wave 2
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Supply Chain models (inventory, orders, delivery, purchasing)
Inventory stock with projections, open orders, delivery performance, and PO schedule lines for operations reporting.
Supply Chain models in Wave 2
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Hard technical fixes: currency, timezone, platform bug
Solved Taiwan Dollar decimal conversion, UTC+8 to plant-local timezone conversion, and a platform-level bug where date-partitioned remote tables silently dropped records.
Data integrity protected across international entities
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Azure Entra authentication migration
Migrated authentication to Azure Entra (IAS) to secure the Datasphere and SAC environment, completed December 2025.
Secure, modern auth layer in place
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Knowledge transfer and handoff documentation
Two on-site visits, report-building training for the internal analyst, and full handoff documentation so JHT operates the platform independently.
Internal team trained and self-sufficient
A look at the work
