Use cases

Examples of how d.AP is put to work.

The use cases here share the same traits: they run across departments, their data sits in several systems, the questions are domain-specific and complex, and they come up ad hoc.

Use cases

Where you can start.

Choose the field closest to your everyday work. Each case shows a question nobody answers today, and how d.AP answers it.

10 Use cases

This ticket sits in fourth level. Does it belong there? What is known about the vehicle and the customer, and what is the next action?

Ticket TCK-40917 concerns a vehicle with an active service restriction, reported in market DE.

The context:

Operating state normal, connectivity lost for 4 days
The affected component is under campaign CMP-238 — 3 further tickets of the same pattern
The reported function is not released in market DE (country availability)

Recommendation: Not a fourth-level case. The cause is the country release — return to third level with a reference to CMP-238.

QuellenOperating stateService statusCampaignsCountry availability

The result

The question is not how a ticket gets solved — it is whether it belongs here at all.

3min

instead of 30 minutes

First analysis at one point of access, not across several tools.

1system

instead of 6 systems

To be opened in order to classify a ticket.

−90%

Less time per first analysis — capacity that returns to problem solving.

Before

Information gathered by hand from several tools, ticket by ticket.
Wrongly escalated tickets occupy the highest support level.
Customer resolution time grows through the misrouting.

With d.AP

First analysis in minutes, not half an hour.
The support-level decision made where the ticket arrives — or one level earlier.
Reporting and further automation on the same model.

Connected data sourcesTicket systemTelemetryService backendCRMCampaigns

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Which markets can order the ventilated seats option, what does it cost there, and which parts does it depend on?

Option OPT-4412 (ventilated seats) can be ordered in 9 of 14 markets.

The context:

Price differs across the markets — importer data on file, reference market DE
The option depends on 3 part groups of the vehicle structure, one of them with limited availability
Not orderable in 5 markets: sales territory without a release

Recommendation: For the 5 markets without a release, the part group is the bottleneck, not the sales territory — a release check is worth it.

QuellenOrder typesVehicle structureImporter pricesSales territories

The result

Every sales question ends in the bill of materials — the most complex structure a vehicle has.

3data worlds

unified in one model

Sales, vehicle structure, importer data.

0Tickets

Bill-of-materials views are queried, not requested from a central team.

1Model

One foundation for every GenAI initiative in sales, not one per initiative.

Before

Sales, vehicle and importer data joined by hand in spreadsheets.
Every view on the bill of materials commissioned and built individually.
Every GenAI initiative wires up its own data connections.

With d.AP

A question about model, options and market answered inside sales, not collected across three departments.
Bill-of-materials views in self-service, not in a ticket.
Domain teams, applications and agents from the same source.

Connected data sourcesSales systemBill of materials / PLMImporter dataConfigurator

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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.

2min

instead of 2 days

Time-to-impact map without 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.

Connected data sourcesSAP S/4SRMMESLogistics APICRM

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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.

312units

instead of 11,500

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

0days

instead of 3 days

Line stoppage — through direct identification of the root cause.

9vehicles

previously reactive

Affected vehicles contacted proactively 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.
Customer complaints are rising 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.

Connected data sourcesPLMCAD metadataMESQMService ticketsField reports

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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.

1question

instead of 5 departments

From checking 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.
Deviation is 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.

Connected data sourcesSAP FI/COSAP S/4AnaplanCRM pipelineSRM · contracts

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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.

1view

instead of 3 systems

Across customers, contracts, and products.

−80%

Sales reporting effort per quarterly review cycle.

Before

Three systems show only one third of the customer.
Cross-sell lists are 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.

Connected data sourcesSalesforceContract systemServiceNowSAP S/4Ticket system

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Which customers on a charging contract had support cases on the same topic last quarter — and whose contract expires within 90 days?

412 customers on an active charging contract had at least one support case on authentication at charge points last quarter.

The context:

For 118 of them the contract expires within 90 days
74 of those cases were solved at the first support level, 44 escalated
The escalated cases cluster on 2 vehicle series sharing one option variant

Recommendation: Approach the 118 expiring contracts before renewal, starting with the 44 escalated cases: that is where churn is most likely.

QuellenContractsCharging sessionsSupport casesVehicle master dataCustomer

The result

Sales and after sales see the same customer for the first time — in the same model.

−90%

per further analysis

Less effort: the model stands instead of being rebuilt per question.

−70%

versus the alternative build

Lower cost for the same analytical capability.

0analysts

Business teams query their own data in natural language.

Before

Customer, vehicle, contract, charging session and support case in separate systems, contracts sometimes in several.
No linkage that reflects the actual process landscape.
Merging, cleaning and analysis by hand; one dashboard per silo.

With d.AP

Questions that were unanswerable before are answered in minutes.
One agreed understanding of the KPIs, across departments instead of per dashboard.
New perspectives on the data without a new data project.

Connected data sourcesCRMContract systemsCharging infrastructureTicket systemVehicle master data

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The copper price is up 12%. Which series and option variants does that hit, how hard, and which suppliers are involved?

Copper sits in 7 part groups across 4 series.

The context:

Highest exposure: series B-3, option variant with the extended wiring harness — +2.1% on material cost per vehicle
Across the quarter's planned production orders: +1.4% material cost on average
3 suppliers cover 80% of the affected parts, two of them with a price escalation clause

Recommendation: Open the negotiation with the supplier without an escalation clause: that is where the uncovered share sits. For series B-3, check the costing before the next price round.

QuellenBill of materialsCommodity contentPurchase pricesProduction ordersOrder types

The result

A commodity price moves. The question is not whether it hits the margin, but where.

4sources

unified in one model

Bill of materials, production orders, commodity content and purchase prices.

1pass

instead of an analysis week

From commodity signal to management decision.

3levels

Exposure calculated through to series, option variant and supplier.

Before

Part prices and commodity prices analyzable separately, in separate tools.
No link to how parts are used, and therefore none to the impact of price changes.
One-off analyses in spreadsheets, rebuilt for every price round.

With d.AP

The impact of a price change calculated down to series and option variant.
Visible which products, series and suppliers are hit hardest.
A negotiating position built on usage and planned production, not on a unit price.

Connected data sourcesBill of materials / PLMERP purchasingProduction planningCommodity data

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d.AP - the Knowledge Layer.

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Who is behind digetiers?

Examples of how d.AP is put to work.

Where you can start.

The question is not how a ticket gets solved — it is whether it belongs here at all.

Every sales question ends in the bill of materials — the most complex structure a vehicle has.

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.

Sales and after sales see the same customer for the first time — in the same model.

A commodity price moves. The question is not whether it hits the margin, but where.

What d.AP delivers.

How we can help you outside of d.AP itself.

Come to us with your biggest challenge.