It's a Game Changer. Brightfield Jason Ezratty President. Allegis Global Solutions Bruce Morton Head of Strategy

Transcription

1 Machine Learning in Services Procurement: It's a Game Changer Brightfield Jason Ezratty President Allegis Global Solutions Bruce Morton Head of Strategy

2 MACHINE LEARNING IN SERVICES PROCUREMENT IT S A GAME CHANGER Jason Ezratty PRESIDENT Bruce Morton HEAD OF STRATEGY

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4 Founded in 2006, Brightfield is a workforce analytics and consulting company that helps the Global 2000 design their workforce precisely right. We couple deep expertise gained from 11 years of consulting with the world's most advanced, AI-driven analytics platform - a one-two punch that uniquely delivers actionable recommendations and proven outcomes.

5 MACHINE LEARNING IS AN APPLICATION OF ARTIFICIAL INTELLIGENCE (AI) THAT PROVIDES SYSTEMS THE ABILITY TO AUTOMATICALLY LEARN AND IMPROVE FROM EXPERIENCE WITHOUT BEING EXPLICITLY PROGRAMMED. ARTIFICIAL INTELLIGENCE DETERMINES MATHEMATICAL EQUATIONS THAT APPROXIMATE REALITY BY FITTING TO AVAILABLE DATA

6 IN OTHER WORDS... GOING FROM THIS

7 TO THIS

8 SO, WHERE DO YOU BEGIN?

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10 DECONSTRUCT THE WORK

11 JOURNEY MAPS AND PERSONAS Need to take lots of information and make sense of it. Influence leaders spending the money on projects. Get beaten up by the boss and the business all day. The paper chase is the most pervasive task. When managers have questions or issues I need to research where contracts are and track them down, read through the contract, research invoices, call the supplier, etc.

12 IMAGINE A World Where You Could Extract and Summarize Usable Data From Sentences in Contract Documents like SOWs Determine the Likelihood SOW Work Assignments are Misclassified Calculate Potential Savings Opportunity if Sourced Via Staff Aug Supply Chain Summarize Savings Potential and Show Potential Impacts to Secondary Metrics

13 SOW ANALYZER STATEMENT OF WORK TEXT EXPECTED DAYS TO SOW COMPLETION SIMILAR SOWS CONTAINED THESE PHRASES TODAY STATED COMPLETION DAYS DAYS ALERTS The Bill Rate for App Developers is 14% lower in Nashville The time to hire for a business analyst is predicted to be 40 days. Consider starting now The bill rate for technicians is 2.5% lower in Raleigh

14 Talent Services Analytics AI Stack PATH TO TALENT DECISION AUTOMATION RELIES ON FULL DATA INFRASTRUCTURE STACK TAXONOMY & CLASSIFICATION BENCHMARKS & COMPARISONS CORRELATIONS & FORECASTS DETERMINATIONS & CONCLUSIONS (Apples to Apples) (What is Normal) (What s Coming and Going) (Get Creative) Which programming skills are on the rise in Financial Services? What should I expect to pay for DBA in NYC? Is our job aging performance improving? What target and max rate card values are ideal for my rate card? How do my talent clusters differ from others in my labor market or industry? Do <90 day assignments fill faster than >90 day assignments? What will happen to my time-to-fill metric if I were to cut rates by 5%? What savings will my rate card and sourcing strategy potentially yield? Which SOW-based worker assignments are most likely misclassified? Which skills are seen in the high end of the market vs. low for DBAs? What should I expect to be paying a DBA in NYC six months from now? How do our workforce planning scenarios compare? Elements and characteristics Conformity and differentiation Time-based and outcomesbased Central tendencies and variances Multi-dimensional and predictive Highly contextual and relevant Trending/time series analysis What-if and why modeling Multi-dimensional forecasting Transactional decisioning Aggregate impact decisioning Scenario-building comparison

15 THE JOURNEY READ SOWs Structure Data Improve VMS structured data Compare to VMS Audit Standardize and categorize SOW data ANALYZE SOW DATA Read MSAs and match SOWs Compare to AP data Identify cost savings opportunities Categorize and analyze contract clauses PREDICT RESOURCE COST Predict roles needed for a delivered work product Confidence scores for the roles required Estimate resources needed for work product PREDICT PROJECT COST Estimate effort for work product Recommend approach for type of SOW (milestone, fixed price, time and materials) Estimate cost for work effort up to one year

16 Multi-Dimensional Forecasting Example

17 THANK YOU

18 Evaluation How-to: Why? How? Your feedback drives SIG Event content By signing and submitting your evaluation, you are automatically entered into a prize drawing From the App 1. Select Sessions 2. Select Day 3. Select General Session with Allegis on Wednesday 4. Click on Clipboard Icon COMPLETE & SUBMIT EVAL

19 Wednesday Morning Keynote Machine Learning in Services Procurement: It's a Game Changer Allegis Global Solutions Download the App: sig.org/app Tweet: #SIGspring18

20 Thoughtonomy

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