d.AP Use Cases: AI for Your Processes

My Tier 1 supplier has unexpectedly failed. Which products and customers are affected? How much revenue is at stake? What are my immediate options for action?

Component KB-2201 (HV wiring harness) is affected, in use at customers OEM North and OEM South.

The specific consequences:

Line L-32 is blocked from day 9 (inventory coverage of KB-2201)
R87 open orders affected - €14.6 million revenue at risk
A KB-2201 has no secondary source - highest risk

Recommendation: Activate secondary source SUB-5588 - lead time 6 days, covers 70% of demand. For the remaining 30%, agree partial deliveries with customers.

QuellenSAP S/4 · BOMSRM · ContractsMES · InventoryCRM · Customers

The result

A supplier failure is no longer a mystery that costs days — it is a solved equation before the line comes to a halt.

70%

Visible coverage via secondary source — preventing downtime.

2days→2min

Time-to-impact map in 2 min instead of 2 days of manual research.

+€14.6M

Revenue secured through fast reaction — revenue risk minimised.

Before

Assessing the situation takes 2–3 days, manually via Excel and e-mail.
Looming contractual penalties and express procurement costs.
Possible options for action only once the analysis is complete.

With d.AP

Impact analysis in 2 minutes, not 2 days.
Recommendations that are immediately actionable — securing revenue and avoiding extra costs.
Risk minimisation through a sound data foundation.

Typical setupSAP S/4SRMMESLogistics APICRMGo-live in 11 weeks

A defect has been reported in component SEN-0743, batch 1400. What is the root cause of the defect? Which products and orders are affected by it? Which actions need to be set in motion?

Batch 1400 (SEN-0743, pressure sensor) comes from SUP-2290 and was tested on testing machine PM-048.

Root cause: testing machine PM-048 was running with calibration deviations since early this morning outside tolerance
In batch 1400, 321 components across 3 assemblies were installed, of which 2 have already been delivered
Affected: 47 customer orders, of which 9 are already in the field with customers

Recommendation: Immediately block batch 1400 in the warehouse, targeted re-inspection of the 9 delivered units instead of a full recall. Root cause can be clearly narrowed down to PM-048.

QuellenPLM · ECR-9842MES · Plant 2/5Service ticketsQM · Test reports

The result

A looming full recall becomes a precise correction before the first customer notices anything.

11,500→312

Full recall avoided — narrowed down to exactly the affected units.

3→0

From 3 to 0 days of line stoppage — direct identification of the root cause

9out of 9

Proactive instead of reactive – affected vehicles can be proactively contacted on day 1.

Before

Full recall looming: 11,500 products affected, as the cause cannot be narrowed down.
2 production lines are stopped for 3 days as a precaution until there is clarity.
Rising customer complaints while root-cause analysis drags on.

With d.AP

Recall limited at the push of a button to 312 precisely identified units — €4.2 million saved.
Series production continues, root cause clearly narrowed down to one machine
All 9 affected vehicles proactively contacted on day 1 — before the first complaint.

Typical setupPLMCAD metadataMESQMService ticketsField reportsGo-live in 14 weeks

Will we be able to hold our EBIT forecast for Q3? If not, how can we still counteract in time with suitable measures?

The Q3 EBIT forecast is at risk of coming in €3.8 million (-6.2%) short. Main driver: Plant South, product line PL-200.

Cause: aluminium raw-material costs +14% since June, not yet carried through into the standard costing
Second effect: the price-adjustment clause with customer OEM Nord (contract KV-3391) should already have kicked in at the start of the month — not yet triggered
41 days left until quarter-end — once triggered, the price adjustment takes immediate effect on open orders

Recommendation: Trigger price-adjustment clause KV-3391 immediately — covers €2.1 million of the gap. The remaining €1.7 million can be offset by shifting 2 planned maintenance budgets into Q4.

QuellenSAP FI/COCRM pipelineSAP S/4SRM · Contracts

The result

The profit warning no one saw coming becomes a measure no one has to fear anymore.

+€3.8million

Profit secured through fast countermeasures.

5→1

From 5 departments involved in checking to 1 question through to resolution.

100%

Auditable: every figure down to the source transaction.

Before

The deviation only becomes visible at quarter-end close, too late for any countermeasure.
Deviations are discussed across 5 departments without anyone knowing the driver.
No data consistency — every system reports different numbers.

With d.AP

Every deviation with driver, source, responsible owner.
One question delivers the complete chain — no cross-department alignment needed.
Ad-hoc response enables timely countermeasures — the forecast holds again.

Typical setupSAP FI/COSAP S/4AnaplanCRM pipelineSRM · contractsGo-live in 9 weeks

Which existing customers currently have the highest cross-sell potential, for which products, and why?

7 accounts identified with high cross-sell potential — top 3: OEM Ost, Zulieferer Baltic, Industriegruppe Rhein.

OEM Ost: 3 assemblies without a maintenance contract, fault reports +40% — potential €480,000 (CM-200)
Zulieferer Baltic: capacity utilisation >90% for 60 days — potential €310,000 (expansion package)
Industriegruppe Rhein: contract term ends in 45 days, no exclusivity commitment — potential €265,000 (upgrade package)

Total potential across all 7 customers €2.4 million.

Recommendation: Prioritised outreach in the order 1. OEM Ost, 2. Baltic, 3. Rhein — highest probability of success based on documented buying signals, no contractual obstacles.

QuellenSalesforceContractsServiceNowSAP S/4

The result

Revenue potential that previously went undetected becomes a prioritized sales list for tomorrow morning.

+€2.4m

Cross-sell realised in 6 months · top-100 account tier.

3→1

Instead of 3 systems — 1 view across customers, contracts, and products.

−80%

Sales reporting effort per quarterly review cycle.

Before

Three systems show three thirds of the customer.
Cross-sell lists manually compiled from a range of different systems.
Quarterly reporting costs 4 weeks of sales effort.

With d.AP

One well-founded cross-system view — contract, service, products, potential.
Lists built from real behavioural signals from the last quarter.
Reporting effort −80% — sales sells instead of compiling data.

Typical setupSalesforceContract systemServiceNowSAP S/4Ticket systemGo-live in 10 weeks

Which systems can be switched off without a single business-critical process getting stuck?

14 systems are potential candidates for decommissioning in wave 1:

9 systems with no active process hook — decommissioning without migration
5 systems with replaceable interfaces — migration in 4-8 weeks

Combined savings potential €8.6 million p.a. across licences and operations.

Risk note: System ERP-Legacy-7 has a hook into Payroll — must be migrated before decommissioning, otherwise the payroll run is at risk in week 47.

QuellenCMDBSAM toolIAMCost centre

The result

Unused systems that kept running for years out of fear of risk can now be decommissioned risk-free.

−€8.6m

Licence & operating costs p.a. after consolidation wave 1.

23→9

Number of redundant tools in the engineering stack.

100%

Audit trail for every decommissioning decision.

Before

Consolidation fails on “we don’t know what’s attached to it”.
Decommissioning decisions are politics.
Licence costs rise quietly in the background.

With d.AP

Systems, processes, costs — in one overview.
Decisions become a matter of fact with an audit trail.
Savings potential per system with a well-founded risk analysis.

Typical setupCMDBSAM toolIAMProcess repositoryCost centre FI/COGo-live in 13 weeks

Which plants are running below plan today, and which order is at risk this week as a result?

Two plants are currently running below plan:

Plant 2: −7.3% (line L-3, 04:12 h downtime yesterday)
Plant 5: −3.1% (no single driver, cumulative effect)

That puts 4 orders > €500k at risk this week. Top risk: order A-91204, delivery date Friday.

Proposal: shift A-91204 to plant 1 — capacity available Wed-Thu, no delivery-date risk, +€18k additional logistics cost.

QuellenMES plant 2/5SAP S/4 PPAPSShop-floor IoT

The result

The delivery date that would otherwise slip unnoticed is now secured days in advance — with a solution instead of just a warning.

+6.4%

OEE on prioritised lines after 6 months.

−90%

Time spent on cross-plant status reviews.

10Plants

Live in one overview — a heterogeneous MES world.

Before

Three dashboards, no cross-plant picture.
Risks are e-mailed in Excel, not computed.
OEE improvement fails on data integration.

With d.AP

One live view across all plants — cross-system.
Agents compute directly on correct database, with a relocation proposal.
OEE +6.4% on prioritised lines after 6 months.

Typical setupMES (4 stacks)SAP S/4 PPShop-floor IoTQMAPSGo-live in 16 weeks

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A supplier failure is no longer a mystery that costs days — it is a solved equation before the line comes to a halt.

A looming full recall becomes a precise correction before the first customer notices anything.

The profit warning no one saw coming becomes a measure no one has to fear anymore.

Revenue potential that previously went undetected becomes a prioritized sales list for tomorrow morning.

Unused systems that kept running for years out of fear of risk can now be decommissioned risk-free.

The delivery date that would otherwise slip unnoticed is now secured days in advance — with a solution instead of just a warning.

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