Data Analytics and the Changing Acquisition Paradigm

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2 Data Analytics and the Changing Acquisition Paradigm Breakout Session #: B14 Moshe Nelson, Jason Whetsell, and Kate Eberle Grant Thorton Date: Monday, July 25 Time: 2:30pm-3:45pm

3 Agenda Introduction Acquisition and Analytics Today Data Analytics Across the Acquisition Lifecycle Live Demonstration 2

4 Introduction Speaker introductions: Moshe Nelson, Senior Manager CPCM Sourcing & Analytics Specialist Aerospace and Homeland Security Jason Whetsell, Manager Former Contracting Officer Supplier Management & Acquisition Data Analytics Kate Eberle, Associate Data Analytics Expert 3

5 Who We Are Grant Thornton LLP is the U.S. member firm of Grant Thornton International Ltd (GTIL), one of the world s leading organizations of independent audit, tax and advisory firms. Through member firms in 113 countries, including over 50 offices in the United States, Grant Thornton partners and employees provide personalized attention and the highest quality service to clients around the globe. Our Global Public Sector (GPS), based in Alexandria, Virginia, is a global management consulting practice providing responsive and innovative solutions to government and international organizations. GPS consists of over 600 professionals with certified subject matter experts in strategic planning, financial management, acquisition management, business and process transformation, performance measurement, and project management. Financial Management & Assurance Performance Transformation Information Technology Decision Analytics Governance, Risk and Compliance Financial Management Operations Transaction Valuation Services Audit and Attest Services Information Assurance Audit Readiness/Remediation Strategy and Organizational Transformation Budget and Planning Performance Measurement and Management Business Process Improvement Acquisition Management Human Capital Management IT Program and Project Management Office IT Strategy and Governance Data Management and Analysis Cybersecurity and Information Assurance Systems Development and Sustainment Applied Analytics Cost and Performance Analytics Financial Business Analytics 4

6 Acquisition Community of Practice Dedicated team of more than 200 practitioners Providing innovative acquisition services and comprehensive solutions to our clients Promoting knowledge sharing on a range of acquisition topics through thought leadership and training events 5

7 Data/Decision Analytics Wikipedia: The discovery and communication of meaningful patterns in data IMFORMS1: The scientific process of transforming data into insight for making better decisions Grant Thornton: The application of modeling and visualization to transform data into intelligence using actionable insights for improved performance, streamlined operations, and strategic decision making: Decision Analytics How have we lived without it? 1 The Institute for Operations Research and the Management Sciences (INFORMS) is the largest society in the world for professionals in the field of operations research (O.R.), management science, and analytics). 6

8 Data/Decision Analytics We haven't lived without it! YOU have been the data analytics processors Consumed Cleansed Analyzed Reported 7

9 Statistics that Set the Stage We need high caliber people Source: Bi-Annual Professional Services Council Grant Thornton Acquisition Policy Survey 8

10 Statistics that Set the Stage We cannot get high caliber people! Source: Bi-Annual Professional Services Council Grant Thornton Acquisition Policy Survey 9

11 We must use technology! Our Goal: Use technology to be the data analytics force multiplier Increase Scalability Identify Trends Determine Correlations Make Predictions Determine Behaviors Identify Outliers Make Defensible Decisions 1 0

12 Analytics Challenges Common challenges 1. We don't have the data we need 2. Data we have is unusable (garbage in, garbage out) 3. Our workload is too heavy to analyze the data the way we need to 4. We can do the analysis efficiently with our current tools if just given more time 11

13 Data Analytics within the Acquisition Lifecycle What and how does my organization buy? Am I performing the way I should be? Enterprise Spend Analysis Strategy & Planning Pre- Award Award Post- Award What and how should I be buying? How are my vendors performing? What should I be buying in the future? 1 2

14 Spend Analysis Attributes of spend analysis How much is being spent? What is the type of spending (IT, Admin, Professional Services, etc.) What type of contracts are utilized Who is involved (Program/Contracting Office/Vendor) 1 3

15 Spend Analysis Methodology Criteria for success A thorough understanding of baseline contract spend with usable information for real time decision making and future planning Identify and Prepare Spend Identify Sources of Spend data Aggregate Spend Data Cleanse Spend Data Analyze Spend Determine Addressable Spend Analyze Spend and Categorize Develop Sourcing Strategies Develop Comprehensive Sourcing Picture 1 4

16 Spend Analysis Challenges Common challenges Data is not easily divided into sourcing categories Vendors are identified by multiple names Data does not go down to an optimum level for analysis Pricing data does not provide enough detail We do not have the tools to analyze the large volume of spend data 1 5

17 Key Data Points for Analysis Organizational Spend Unmanaged Managed Open Market Sole Source Awards (e.g., Under Micro- Purchase) BPA/IDIQ A top-down and bottom-up approach is required for a comprehensive picture of spend 1 6

18 Spend Analysis Force multiplier Technology + Institutional Knowledge = Magnified Results 1 7

19 Spend Analysis Benefits Benefits of the proposed solution More in-depth understanding of spend Force multiplier through technological innovation Provides short and long-term planning information Demand driven decision making Cost savings identification 1 8

20 Data Analytics within the Acquisition Lifecycle What and how does my organization buy? Am I performing the way I should be? Enterprise Spend Analysis Strategy & Planning Pre- Award Award Post- Award What and how should I be buying? How are my vendors performing? What should I be buying in the future? 1 9

21 Procurement Operations What is procurement operations? Day-to-day award and administration of contracts, task orders, BPA calls, etc. Enterprise Spend Analysis Strategy & Planning Pre- Award Award Post- Award 20

22 Procurement Operations Criteria for Success A thorough understanding of contractor, staff, stakeholder, and enterprise performance to influence change and make decisions Select Collect Analyze Review Design Priority Measures Streamline Data Collection Rationalize Data Analysis Organize Impact Reviews Identify acquisition and mission priorities Select priority measures Map data sources and collection flows Collect data; set performance targets Refine data quality controls Establish repeatable data analysis processes Design role-based dashboards Establish governance Facilitate internal discussions of performance variances 21

23 Pre-Award Operations Need identification through contract award Requirements development Solicitation development and issuance Evaluation and award 22

24 Pre-Award Operations Common challenges 1. Delayed requirements development 2. Inefficient procurements 3. Ineffective allocation of workload 2 3

25 Pre-Award Operations Common challenge #1 Delayed requirements development Did you award the contract yet? Uhhh You sent me the SOO 2 days ago. 24

26 Pre-Award Operations Common challenge #2 Inefficient procurements Did you award the task order yet? Uhhh Not yet. We've only been evaluating proposals for 9 months. 25

27 Pre-Award Operations Common challenge #3 Ineffective allocation of workload Did you enter your CPARS? Uhhh Have you seen how many new procurements I'm working on? 26

28 Pre-Award Operations 27

29 Pre-Award Operations Benefits Identify process bottlenecks Target resource allocation and prioritization efforts Influence change 28

30 Post-Award Operations Common challenges Use of relevant past performance in decision support Timeliness and quality of CPARs entries 29

31 Post-Award Operations Post-award accountability increases collective buying power Performance scorecards help improve CPARS entry rates and quality 30

32 Post-Award Operations 31

33 Post-Award Operations Benefits of the proposed solution Apply performance data to vendor relationship management Use on-hand past performance to increase efficiency of contract awards Improve CPARS entry rates and accuracy Identify opportunities for requirements standardization and cost savings 32

34 Interactive Demonstrations - Enterprise Spend Analysis What aspect of spend analysis are you most concerned with? Text A, B, C, or D to the number 22333: A Where am I spending the most by office and region for product "A"? B What is my office supply price differentiation by region for product "B"? C What are my spend patterns for product "C" over a year? D Which product should I focus on if I am seeking to save the agency money? 33

35 34

36 Interactive Demonstrations Pre-Award Operations Which pre-award challenge are you most interested in exploring further? Text A, B, C, or D to the number 22333: A Which program office division is probably responsible for current procurement delays? B Which contracting officer has available capacity to take on new work? C Which procurements require additional attention to get back on track from a schedule perspective? D Which procurement method (open market, GSA, etc.) likely requires process improvements or adjustments to target cycle times? 35

37 36

38 Interactive Demonstrations - Post-Award Which vendor management area are you most interested in? Text A, B, or C to the number 22333: A Of the vendors producing product "A", which may need additional attention? B Of the vendors producing product "B", which exhibits the best value (price and timeliness)? C Which of vendor 2's production plants are exceeding the performance benchmark for product "B" 37

39 38

40 Questions? 39

41 Contact Information Moshe Nelson (Phone: , Jason Whetsell (Phone: , Kate Eberle (Phone: , 40

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