Analytics For Non-Analysts The Value Of Predictive Analytics For - PowerPoint PPT Presentation

Analytics For Non-Analysts The Value Of Predictive Analytics For Digital Supply Chains Randy V. Bradley, PhD, CPHIMS, FHIMSS The University of Tennessee rbradley@utk.edu @randyvbradley linkedin.com/in/randyvbradley +1-334-354-5966 2018 MHI ANNUAL CONFERENCE

Agenda Overview 1. Top supply chain challenges 2.The quest for and challenge of visibility 3. Linking analytics and Nextgen supply chain 4.Got data? Get insights -- that are actionable and impactful 2018 MHI ANNUAL CONFERENCE 3

Top Supply Chain Challenges 2018 MHI ANNUAL CONFERENCE 4

Means, Not Ends: Transparency and Visibility SUPPLY CHAIN SUSTAINABILITY TRANSPARENCY TRACEABILITY INTEGRITY VISIBILITY SUPPLY CHAIN RISK MANAGEMENT 2018 MHI ANNUAL CONFERENCE 5

Attributes of NexGen Supply Chains 1 6 Digital Transparent 2 7 Connected Secure and trusted 3 8 Collaborative Agile, adaptive, responsive 4 9 Always-on Effective and efficient 5 10 Forward-looking analytics Safe and sustainable 2018 MHI ANNUAL CONFERENCE 6

We as a company didn’t go to bed one night and say , “ We can’t be an industrial company anymore. We need to be more like Oracle. We need to be more like Microsoft.” It happened more on an evolutionary basis, really based on the industries we’re in and the technology we serve. So industrial companies are in the information business whether they want to be or not. This is going to happen in the industrial We want to treat analytics like it’s as core to the company over the space. next 20 years as material science has been over the past 50 years. We need to...share outcomes with our customers...we have to add technology, we have to add people, we have to change our business models ~Jeff Immelt, General Electric Chairman and CEO 2018 MHI ANNUAL CONFERENCE 7

What Are We Seeing? • 10% growth in electronic linkages (EL) with customers • Up to 25% growth in EL with suppliers • Increase in and greater emphasis placed on real-time access to data 2018 MHI ANNUAL CONFERENCE 8

What Are We (Still) Seeing? • Digital business journeys hampered • Insufficient business-savvy IT and analytics staff • SC personnel lack requisite current gen IT and analytics skills and knowledge •Top drivers of ERP (“operational backbone”) adoption • Streamline and improve business processes • Enhance data accuracy and consistency • Improve SC efficiencies 2018 MHI ANNUAL CONFERENCE 9

Survey Participants for 2018 MHI Annual Industry Report 1,100 manufacturing and supply chain industry leaders on supply chain innovation 50% 75% 47% manufacturers, distributors CEO, Vice President, General Manager, or annual sales in excess or service providers Department Head of $100 million, and 10% reporting $10 billion or more 2018 MHI ANNUAL CONFERENCE 10

2018 MHI ANNUAL CONFERENCE 11

Key Survey Highlights 2018 MHI ANNUAL CONFERENCE 12

Most Common Uses of IoT in the Supply Chain 2018 MHI ANNUAL CONFERENCE 13

Big Data is Relative…Not Absolute Big Data ( Noun ) When volume, velocity, and variety of data exceed an organization ’ s storage or compute capacity for accurate and timely decision-making 2018 MHI ANNUAL CONFERENCE 14

Current Analytics Approach: MST = OBL O ne M ultiple B ig S ources of Analytics Engine T ruth L ie 2018 MHI ANNUAL CONFERENCE 15

The Role of Predictive Analytics: Truth Teller M ultiple Analytics S ources of The Truth Engine T ruth 2018 MHI ANNUAL CONFERENCE 16

The Role of Predictive Analytics: Truth Teller M ultiple V arious Analytics S ources The Truth Engine I nsights of T ruth 2018 MHI ANNUAL CONFERENCE 17

From Predictive to Prescriptive “Prescriptive analytics provides us with what’s the best possible le act ction I I can take today in in lig light of what I I anticipate happening tomorrow. . But what good is is it it to predict what you cannot act upon?” 2018 MHI ANNUAL CONFERENCE 18

The Role of Prescriptive Analytics: Value Realizer Various Experience Analytics Analytics & Insights Engine Expertise Engine 2018 MHI ANNUAL CONFERENCE 19

Analytics Value Limiters • Data streams • Questions • Strategy 2018 MHI ANNUAL CONFERENCE 20

How well does your organization manage capturing, processing, and integrating data streams from multiple sources? A. We have no formal mechanism for measuring B. Poor C. Fair D. Good E. Excellent F. Are you kidding me…I have no idea! 2018 MHI ANNUAL CONFERENCE

What types of questions do you seek to answer? A. What happened? B. How many, how often, where…? C. What exactly is the problem? D. What actions are needed? E. Why is this happening? F. What will happen next? G. What if we try this? H. What’s the best that can happen? 2018 MHI ANNUAL CONFERENCE

Got Data … Get Insights What Type of Questions Are You Asking? 2018 MHI ANNUAL CONFERENCE 23

Types of Questions and Analytics Descriptive Predictive Prescriptive Questions What happened? Why is this happening? What should I do? What’s happening? What will happen next? Why should I do it? What exactly is the Why will it happen? What’s the best that can problem? happen? What actions are What if we try this? needed? • • • Enablers Ad hoc Reports Data Mining Optimization • • • Dashboards Text Mining Simulation • • • Data Warehousing Web/Media Mining Decision Modeling • • • Alerts Forecasting Randomized Testing Outcomes Well defined business Accurate projections of Best possible business decisions problems and the future states and and transactions opportunities conditions 2018 MHI ANNUAL CONFERENCE

Got Data…Get Insights Descriptive Diagnostic Predictive Prescriptive SURFACE Predictive Descriptive What happened? What will happen? FUTURE PAST Prescriptive Diagnostic DEEP What should I do? Why did it happen? 2018 MHI ANNUAL CONFERENCE 25

Does your organization have a defined analytics strategy? A. Yes B. No 2018 MHI ANNUAL CONFERENCE

Data-Driven Decisions? When you say or hear data-driven decisions, what do you mean/is meant? 2018 MHI ANNUAL CONFERENCE 27

Data-Driven Decisions? Do you mean… Data Drive Decisions? 2018 MHI ANNUAL CONFERENCE 28

Data-Driven Decisions? Do you mean… Data Should Drive Decisions? 2018 MHI ANNUAL CONFERENCE 29

Data-Driven Decisions? Do you mean… Data Systems Make the Decisions? 2018 MHI ANNUAL CONFERENCE 30

Data-Driven Decisions? Do you mean… Data Should Support Decisions? 2018 MHI ANNUAL CONFERENCE 31

Data-Driven Decisions? Do you mean… Data Should Support Decision-makers? 2018 MHI ANNUAL CONFERENCE 32

Data-Driven Decisions? Do you mean… Data Influence the Decisions? 2018 MHI ANNUAL CONFERENCE 33

Data-Driven Decisions? Do you mean… Data Inform Decisions? 2018 MHI ANNUAL CONFERENCE 34

Data-Driven Decisions? Do you mean… Data Should Help Analyze Decisions? 2018 MHI ANNUAL CONFERENCE 35

Got Data…Get Insights ISSUE INSIGHTS ACTION ▪ Product persistence ▪ Identify idle products ▪ Change production schedules ▪ Implement sales incentives ▪ Returns & trade ▪ Monitor trades & returns ▪ Impose returns authorization management via authentication ▪ Detect suspicious activity ▪ Prevent parallel trade ▪ Buyer & supplier ▪ Gather simple and ▪ Target regions based on engagement complementary purchasing purchasing trends trends ▪ Develop solutions based ▪ Collect customer on consumer response data consumption data 2018 MHI ANNUAL CONFERENCE 36

Got Data…Get Insights Businesses can gain true-time insights from rich data: Presents an • Identify product persistence opportunity to collect o Dwell time data for better value o Product expiry chain insights • Improve returns and trade management • Increase customer and supplier engagement 2018 MHI ANNUAL CONFERENCE 37

THANK YOU! Randy V. Bradley, Ph.D., CPHIMS, FHIMSS rbradley@utk.edu @randyvbradley linkedin.com/in/randyvbradley +1-865-974-1761 +1-334-354-5966 2018 MHI ANNUAL CONFERENCE