Think of an SCM-related business process in an organization that interests you which contains at least one decision task that is not presently automated but that could potentially be. Let us call it the "focal decision task".
(For example, refer to the in the insurance claim process in the reading “Embed Analytics in Decision Processes” illustrated in Figure 7-1.)
Describe the business process and the focal decision task and provide a truncated diagram of the business process (e.g., labeled boxes and arrows).
Suggest a possible automation for this decision task. Include what data will be used and whether the decision should be fully automated, automated with exception/overrides, or assisted after the change - and why.
Describe what technology(ies) and/or algorithm(s) could be put to use to inform the decision process your suggested above.
Focal Decision Task: Supplier Contract Renewal Recommendation
Currently, this task is manual. A Procurement Manager reviews the Supplier Performance Scorecard, which includes metrics like On-Time Delivery (OTD), Defective Parts Per Million (PPM), and Price Variance. The manager applies their subjective experience, historical relationship knowledge, and an understanding of the current market risks to determine the recommendation (Renew, Renegotiate, or Terminate).
Suggested Automation
The focal decision task should be automated with exception/overrides.
Automated Decision Rationale
The decision should be automated with exception/overrides because:
Efficiency: It automates the majority of routine decisions for high-performing (clear Renew) and low-performing (clear Terminate) suppliers, freeing up the manager's time.
Risk Management: It ensures that objective, pre-defined organizational risk thresholds (e.g., if a supplier’s OTD drops below 90% for two quarters) immediately trigger a Renegotiate or Terminate recommendation, reducing human oversight error.
Need for Context: The human manager still needs the override capability to handle exceptions, such as:
Single-source suppliers where termination is not feasible.
Suppliers with a low score due to an extenuating external event (e.g., a natural disaster) rather than internal failure.
A supplier with a mixed score (e.g., excellent quality but poor cost) where subjective negotiation strategy is required.
Data Used for Automation
The automation requires using integrated data from various enterprise systems:
ERP/MRP System: On-Time Delivery (OTD) % and Fill Rate %.
Quality Management System (QMS): Defects Per Million (PPM), Reject Rate, and Corrective Action Request (CAR) closure time.
Financial/Costing System: Price Variance % against the negotiated benchmark, and Total Cost of Ownership (TCO) data.
Risk Management Database: Supply Market Risk Score (e.g., geopolitical stability, financial health) for the supplier's region/company.
Technology and Algorithms
The automation of the "Supplier Contract Renewal Recommendation" decision task would utilize a combination of analytics technologies and algorithms:
1. Technology: Business Rule Management System (BRMS)
A BRMS would be the core technology. It executes the logic to assign the initial recommendation:
Logic: A predefined, transparent set of "If-Then-Else" rules based on organizational policy.
Example Rule: IF (OTD ≥ 98%) AND (PPM ≤ 500) AND (Risk Score is Low) THEN Recommend RENEW.
Example Rule: IF (OTD <90%) OR (PPM >5000) THEN Recommend TERMINATE.
2. Algorithm: Weighted Multi-Criteria Decision Analysis (MCDA)
To handle the more nuanced Renegotiate decisions, a Weighted Scoring Model (MCDA) algorithm could be used:
Process: Each KPI (OTD, PPM, Cost) is assigned a specific weight based on its importance to the organization (e.g., Quality gets a higher weight than Cost).
Output: The system calculates a Total Weighted Score (TWS).
Decision: If TWS falls within a specific range (e.g., 70-85), the recommendation is Renegotiate, and the model can highlight the lowest-scoring categories to focus the negotiation effort.