You May Get
Sources of Insight
I don't know
Limited use in one area only
Broad use in multiple areas
I don't know
Minor investment to test ROI
Major investment within the next 24 months
Major investment within the next 12 months
We extract data from our ERP to analyze Spend
Less than 50%
More than 95%
Annually (or less frequent)
Fully Automated (little or no manual operations)
Track market indices for only our most strategic categories.
Track market indices for most or all relevant categories.
Market indices are analyzed by BI tools and supplemented by third party reports.
Market indices, analyst reports, and other sources are automatically fed into category-specific applications.
Category-specific applications are enabled by AI to provide and execute recommendations.
Informally through traditional media and publications.
Some automated alerts monitor our most strategic suppliers
Automated alerts setup for all suppliers.
Artificial Intelligence agents monitor alerts to provide and execute recommendations.
Less than 150
151 - 400
401 - 1000
1001 - 1500
More than 1500
Less than 20%
21% to 30%
31% to 50%
51% to 70%
More than 70%
Less than 30%
30 - 50%
50 - 75%
75 - 90%
More than 90%
Primarily ad hoc, not executed on a regular pre-defined schedule
Primarily Annual events with most suppliers
Quarterly events for key sub commodities or groups of suppliers.
Weekly events executed for key sub commodities or suppliers.
Continuous sourcing with suppliers or sub commodities as needed based on market conditions.
Less than 30%
30 - 50%
50 - 75%
75 - 90%
More than 90%
Primarily price or cost-focused negotiations
Focus on long-term partnerships
Competitive situations are leveraged whenever possible (e.g. 2 or more suppliers compete for awards)
Target costs or external benchmarks are shared with suppliers
Cross-functional considerations (technology, risk, quality) are considered
Artificial Intelligence provides negotiation recommendations
Less than 10 Days: We're integrated with suppliers and utilize an AI- enabled platform to automate many of the event tasks
10 - 30 Days: Most events are "two bids and a buy"
30 - 60 Days: We keep events small and digestible and utilize tools to ease baseline collection and analysis
More than 60 Days: Tools and techniques allow us to consolidate into fewer, much larger events that take more time to collect bids and obtain internal approvals
Less than 2 days: Our systems are all integrated with data cleansed and maintained on a near continual basis, and our AI platform processes baseline preparation automatically.
2 - 5 days: Our systems are all integrated with data cleansed and maintained on a continual basis
5 - 15 days: Our events are very small and suppliers help provide the data
15 - 30 days: Data is extracted from a Spend cube and/or purpose-built category management tools, so a majority of the time is fine-tuning and getting stakeholder approval.
More than 30 days: Need to pull data from multiple sources, requires manual manipulation, then push into a reporting tool to gain stakeholder approval.
Less than 1 day: We are on stand-by to run an event on any given day given market conditions.
1 - 5 days: Our events are simple and we typically start from what was done previously.
5 - 14 days: We typically start from previous events / templates, but review for updates.
More than 14 days: We reference previous events / templates, but given the large scope of events we revisit and potentially redesign events.
Less than 1 day: Our AI tools provide insights and analysis for Category Manager review, and distribute feedback.
1 - 5 days: Our events are limited in scope so we can typically churn through analysis and feedback quickly, albeit manually.
3 - 5 days: Our sourcing tools provide nice reports and collaboration tools to analyze bids, then make feedback fairly easy to distribute.
5-10 days: Our sourcing tools help aggregate bid information, but we analyze in a separate BI tool then distribute feedback.
More than 10 days: We run large events and although our category-specific tools help aggregate bid data and analysis, it takes time to interpret the results then distribute internally to prepare feedback.
Less than 1 day: Our AI tools identify negotiation opportunities which are communicated to suppliers who we share an open-book relationship with.
1-3 days: Although we manually prepare for negotiations, the scope is limited so we're able to complete it quickly.
3-5 days: We extract the data from our sourcing tools to feed our BI tool and/or create our negotiation materials.
5-7 days: Our sourcing tools help identify negotiation opportunities.
More than days 7: We run large events and although our category- specific tools identify negotiation opportunities, it takes time to align internally and prepare for large-scale negotiations.
The Category/Commodity Manager
The Category/Commodity Manager + supporting business analysts
Cross-functional alignment with input from manufacturing partners, engineering, supply chain, and finance
Automated commodity/category strategy digital playbooks sourced from an AI/cognitive platform?
Less than 2 days: Our AI tools aggregate bid data, provide data insights, and present those insights and recommendations to Category Managers to approve.
2 - 6 days: Although we manually analyze and award it goes fairly quickly because our events are limited in scope
6 - 10 days: Our final analysis is executed outside our sourcing system, then distributed to decision makers, and awards are made.
10 - 14 days: Our sourcing tools allow us to analyze and award quickly, so most of time is spent reviewing with stakeholders and gaining internal approvals.
More than 14 days: We run large events and although our category- specific tools help, it takes time to conduct final analysis to make award decisions, distribute those to stakeholders, and announce award decisions.
Historic Data from enterprise systems (ERP, Business Intelligence, Spend Analytics)
Benchmark pricing for standard parts from distributors or third parties.
Contextual insights around supplier financial health, raw material input costs, foreign exchange, news sources.
Market intelligence from third-party research, analysts, published indices
Community insights from peer companies engaged with similar commodity groups or strategic suppliers
Data or research collected from company's supplier network
Attribute-based, bottoms up "should cost" models
AI-generated risks and opportunities
Relevant benchmark/market trned data, poor supplier relationships
RFX solution to efficiently execute and manage bids, lack of negotiation skill/guidance
Challenging commodity market environments
Underlying business externalities (e.g. forex, tariffs/trade, cutstomer markets, global economy)
Excellent - Procurement is well-regarded and is seen as a key business partner
Fair - Procurement has more influence with some functions than others
Poor - Procurement operates is silos and has difficulty collaborating
1 (Limited or no input during design phase, operating in a silo)
3 (Visibility and input into development decisions and timelines)
5 (Full data consistency and visibility across all functions), supply chain participates in trade-off decisions
Here's an interesting quiz for you.