Design Thinking · SAP Fiori · Supply Chain Planning
How a global printing ink manufacturer built a Design Thinking-led Fiori app in 9 weeks and hit 350% ROI
Global Printing Ink Manufacturer Delivered 2018
Mindset delivered a Design Thinking-led SAP Fiori production forecasting app for the ink manufacturer in 9 weeks. Within one year, the ink manufacturer measured a 350% ROI. Within 6 quarters, the app was running at 100+ locations for 120+ users.
By the numbers
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350%
One-year ROI
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9 weeks
From kickoff to working app
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100+ locations
Scaled to within 6 quarters
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50%
Expected transportation cost reduction
Before
Forecasting gaps driving avoidable cost
- Incorrect production forecasts created unexpected supply issues and last-minute schedule changes.
- Poor order consolidation drove up transportation costs.
- No purpose-built tool to give planners the visibility they needed.
After
A Fiori app built around real users, scaled globally
- SAP Fiori production forecasting and order consolidation app live in 9 weeks.
- Rolled out to 100+ locations and 120+ users within 6 quarters.
- 350% ROI measured at the one-year mark, with transportation cost savings on track.
“...we measured the payback of the project at around 1 year, and the ROI to date is 350%”
Built on
- SAP Fiori
- Design Thinking
- Agile / Rapid Prototyping
- Jira
Why this matters
the ink manufacturer chose agile over waterfall specifically because shorter sprints meant realizing benefits earlier. The bet paid off: 9 weeks to go-live, a measured 350% ROI in year one, and a design thinking practice that became part of how the company works.
The challenge
In chemical manufacturing, getting production forecasting wrong is expensive. Incorrect forecasts ripple out as unexpected supply issues, last-minute changes to production schedules, and avoidable transportation costs as orders get rushed or poorly consolidated.
the ink manufacturer, one of the world's largest producers of printing inks, coatings, and pigments, needed an application that would improve production forecasting and help consolidate orders to reduce transportation spend. The problem was real and urgent, but the solution space was not obvious. They needed a team that could get in, understand the work, and ship something fast.
the ink manufacturer had a choice of approaches. One option was a conventional waterfall project. The other was an agile, Design Thinking-first model that would front-load user understanding, generate and discard ideas quickly, and deliver working software in shorter cycles.
What we did
Mindset ran the engagement as a full Design Thinking process paired with agile delivery. The Explore stage produced user personas that grounded every decision in the actual work of the planners using the app. Discover assessed existing technical capabilities and expanded the solution space before narrowing to feasible approaches. In the Design stage the team ran rapid prototyping cycles: build an idea, test it, throw out what did not work, and improve what did.
The result was a SAP Fiori-based application for production forecasting and order consolidation. The rapid prototyping approach meant the final design reflected real user needs, not assumptions. The whole process, from kickoff to a working app, took 9 weeks.
After go-live Mindset provided ongoing technical support as the rollout expanded. The engagement itself started with a smaller Design Thinking workshop in 2017 before growing into the full InPlant Planning build.
The outcomes
the ink manufacturer went live and then scaled. Within 6 quarters the app was running at more than 100 locations with more than 120 users. That kind of rollout spread does not happen unless the tool actually works for the people using it.
On the business side, the numbers came in. the ink manufacturer measured the payback period at around one year. The ROI at the one-year mark hit 350%. Transportation cost reduction came in at an expected 50%, driven by the improved ability to plan ahead and consolidate orders.
The broader impact showed up in how the the ink manufacturer team talks about what happened. Years later, the design thinking approach Mindset introduced had become part of how the ink manufacturer approaches process improvement across the board.
On stage & in the press
If we built this today
Concept · not delivered scopeForecasting and load consolidation, agent-led.
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.
This case fixed expensive forecast misses that turned into supply surprises, rushed schedule changes, and half-empty trucks, so the modern build puts an agent on exactly that loop.
The Joule agent
Demand Sensing Assistant
Reads live demand signals, open orders, and plant capacity across the network, then proposes a tighter production forecast and consolidates shippable orders into fuller loads. It flags where a forecast miss is about to force a last-minute schedule change or a half-empty truck.
SAP S/4HANA, SAP Integrated Business Planning, SAP Fiori · PROPOSE · Transportation cost per shipment and forecast accuracy
The Fiori app
Joule "AI-Assisted Supply Optimization" in SAP IBP
The planner works in the same Fiori planning view, but Joule sits inside it and suggests forecast adjustments and consolidation moves with the reasoning shown. A human approves before anything changes the plan.
Embedded in the Fiori launchpad
The data product
Cloud ERP Intelligence with a supply-chain data product
Grounds the agent in actual order, inventory, and logistics history across all the plants so its forecast and consolidation calls reflect real network behavior, not a single site. The data product keeps demand and shipment signals in one governed place.
Intelligent Application on SAP Business Data Cloud
We'd mine the current planning and order flow in SAP Signavio first, map the app and integration estate in SAP LeanIX, and let MIND accelerators carry the working Fiori logic from the old build into the new one.
What we built
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SAP Fiori production forecasting app
A Fiori-based application for production forecasting and order consolidation, designed to reduce last-minute schedule changes and cut transportation spend.
Delivered in 9 weeks
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Design Thinking engagement
Full three-stage process: Explore (user personas), Discover (technical assessment and solution-space expansion), Design (rapid prototyping with agile development).
User-grounded design before a line of code
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Rapid prototyping cycles
Ideas generated, tested, and discarded or improved quickly, pairing Design Thinking with 3-4 week agile sprints so the final solution reflected what users actually needed.
Shorter cycles meant earlier benefit realization
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Enterprise-wide rollout
Scaled from a single-location proof of concept to 100+ locations and 120+ users across the the ink manufacturer global operation.
100+ locations, 120+ users within 6 quarters
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Ongoing technical support
Mindset continued to support and maintain the application after go-live as the rollout expanded.
Continuous support through scale-up
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Design Thinking workshop
A smaller scoped Design Thinking workshop in 2017 that established the methodology and led directly into the full InPlant Planning build.
Foundation for the full engagement
A look at the work