Date: 16.01.2026 (2026-01-16)
Klaus-Peter Peya (16.01.2026) Context: • https://www.linkedin.com/in/klaus-peter-peya-784524192/ • Sector CFO International Seals @ DIPLOMA PLC (FTSE 100) (1k+ Employees) • Bensheim, Hesse, Germany • Company London, UK • My message: • ich bin auf Ihr Profil gestoßen, da Sie super viel Erfahrung in verschiedenen Finance-Rollen haben - v.a. bei KPMG und als CFO. • • Wir stehen aktuell vor einer Produktentscheidung und möchten gerne die Perspektive aus der Praxis einbeziehen: Wo sehen Finanzteams künftig den größten Mehrwert durch KI: bei der Unterstützung des Monatsabschlusses oder im Bereich Einkauf & Beschaffung (Transparenz, Kosteneinsparungen, Lieferantenmanagement)? • • Zum Hintergrund: Wir haben proprietäre KI-Modelle zur End-to-End-Automatisierung der Kreditorenbuchhaltung entwickelt. Das Finanzteam muss hierbei kaum noch eingreifen; nur bei Unklarheiten wird eine gezielte Freigabe an die entsprechende Abteilung gesteuert - direkt mit dem vollen Kontext für eine fundierte Entscheidung. • • FUP • Wir entwickeln eine KI-Finance-Software für das Monthly Closing mit dem Ziel: Closing-Zeiten und manuellen Aufwand um ~50% reduzieren: • a) Fehlende Rechnungen & Informationen automatisch intern & extern einsammeln (basierend auf Reconciliation) • b) Approvals risikobasiert anstatt mit starren Freigabeprozessen • c) Dem Approver immer den kompletten Kontext mitgeben (Budget, Zweck, Historie, Abweichungen, etc.), damit Entscheidungen in Sekunden getroffen werden können • • Falls Sie Zeit haben, würde ich gerne Ihr Feedback zu Ihren grössten Challenges und unserem Ansatz hören. • Reply: • Hallo Herr Brandstätter, wir können gerne am Freitagvormittag sprechen. Ich würde tatsächlich Teams bevorzugen, damit sie mir einen visuellen Überblick geben können. • Viele Grüße • Klaus-Peter Peya
Notes: • Notes: • • Challenges for his roles: he is responsible for 1 sector • 4 platform business -> 30 different entities • Sector: 11 different ERP systems -> goal: they want 3 different ERPs • Challenge: having live insights in real time • Revenue, margin etc. • Revenue is good via BI tool for ERP • Profitability, gross margin is tricky • Cost of inventory vs. shipment -> BI tool is good • Distribution of overhead is tricky • AI in accounting was not a big topic so far -> they are very decentralised • They use AI towards the customer for Wertschöpfung • Kunde ruft an und will technische Beratung -> they took their internal database -> they did it with AI (reduced call time by 50%); Premium partner can order without calling • Complex distribution centers STUs -> high inventory capital bindung (seasonality, 28k products) • They use Slimstock: 40 Mio EUR -> 26 Mio EUR -> kann man reinvestieren; 100k setup costs and 50k per year • He thinks very commercially -> optimise a finance process is not as important as optimising the business • A lot of the features will come via next update of ERPs -> he does not want to invest heavily - but they are open to test products • We have to differentiate from SAP, Oracle -> a lot of companies run on one ERP • Tackle the companies that have fragmented systems • Themen: • Rechnungen ohne Bestellbezug -> Document Management System for Approvals -> AP can only book when approval is done • AP: • Asian invoices are very difficult • There is no standard • Anomaly Detection: • Fraud is getting better • Standardkontrollen -> schütze Stammdaten -> processes how to change Stammdaten -> Link with Stammdaten is super important • We have Aufwandskonten -> Vorratskonten in produzierenden Unternehmen -> it starts with Business Model of the company -> • Subledger getrieben • Some do it on GL Ebene and some on Sub Ledgers • Industrieunternehmen: • They outsource stuff to other companies • Via supplier you can say that stuff goes in Vorrat • Often the Accounting is handed over with Bestellnummer -> then AI has to just check; • Bestellbezug can be done without AI • Dauerbestellung: • Früher: Verträge • They have a Verantwortung ggü GER as Standort • Strategic direction: • AI should be seen as value driver - not cost reduction • He would go for procurement - not to accounting -> there is more value • He was a lot in SMEs • Monthly end: • There is a lot of complex topics -> a lot of judgment required -> he does not see that much value in that • Some bookings can be automated - most ERPs offer that -> no AI required • Rückstellungen, Afa Läufe (linear vs. Auslastung basiert), • Monthly close duration: mainly that finance team is waiting for departments to provide information • Account Reconciliation: big potential - Check out Blackline (Account reconciliation tool from US) - Balance sheet, P&L accounts -> you create a structure with all accounts and then they offer • Often GL account -> if there is no Subledger - Blackline can eintragen Rückstellungsspiegel in das System • Blackline: also reminds people • Big potential: bookings from the whole month -> Rückstellungen • Note: US driven -> not done in many SMEs in GER • Bank reconciliation: 127 Rechnungen - AVIS - and one payment -> could be a big topic (they had 3 AR FTEs for 65 Mio - per day 100 invoices) • There are ERP tools that can do that • He does not like the automatic dunning process • They had pure B2B - eg automotive -> automatic emails are not the solution • Negotiate that they pay part of it - pay 30% of it • Procurement: • Often yearly Preiserhöhung -> Schreiben of Supplier that they will increase their prices by 3 to 5% -> Procurement does the negotiation • There are different reasons that price does not match with PO -> they send it to Procurement -> not talk to the supplier • Could be that the procurement forgot to update the supplier contract • Raw material preisschwankungen -> weekly changes • Negotiation: • Past: Analyse volume, • Create slide • Negotiation power: looking in the future -> that is difficult to get by AI • Check Slimstock as inspiration -> he uses the same logic for negotiations: seasonality and product groups that were related (sell 1 product -> likely that 2 further products are sold) • Slimstock also took weather data (e.g. water pumps or agriculture products) - before Slimstock: hard coded min max thresholds • He is responsible for 35 companies • Biggest one 90 Mio (20k Artikel) -> professional supplier management -> rate supplier yearly by criteria (lieferzeit, etc.) • They have supplier of choice -> for certain articles you should have different supplier • China: cheap, but long delivery time • GER: expensive, but short delivery time • Acquisition of a company is always based on a strategy • Company strategy is in a powerpoint information -> for forward looking negotiations -> Department Leaders take the tasks for the future -> can be processed by AI • High level: 30% growth because we grow ABC • Then Sales etc. defines which products • Procurement understands he needs more volume • Manufacturing understands if they can produce it - often a problem • Potential for AI: take the information where Sales and Procurrement synch and what is sold and what they need • Potential: New products: • Sales estimates how often they sell a new product • Complementary products -> could be supported AI based • Very manual task -> could be potential of AI • Why can BCG reach huge potential • Volume vs. Market Power • Automation: • • Biggest objections / challenges in his daily life? • • Most valuable flows for him? • • Context: team setup? internal and external? • • Which tasks are the biggest pain? With magic wand -> what would he solve? • • Which tasks would he focus on? • • Do they already have automations? Which ones? How well do they work? • • Which companies would he target? • • General feedback to pitch? •