Report Details: The research for this report was conducted via an online survey from October 24 – December 12, 2017. Surveys were conducted among a mix of business users (manufacturers, retailers, and wholesalers/distributors/co-operatives, n=56) and vendors (software providers, consultants, and third-party logistics providers, n=53), and others (academics, analysts, unemployed, and others, n=28). The analysis focuses primarily on users and vendors. All respondents were required to be at least a little familiar with analytics strategies. Objective: To understand current analytics strategies and where companies are investing. NOTE: analytics strategies (technologies and tactics) include the Internet of Things (IoT), cognitive computing, Hadoop, Blockchain, data visualization, text mining, data lakes, software robots, unstructured data mining, sentiment analysis, and drones, etc. Highlight: New forms of analytics offer great potential and opportunities. The greatest value will happen when companies consciously test and learn and redefine processes based on new capabilities. Core to this journey is the alignment of IT and business with a focus on value and business outcomes.

1. Analytics Strategies Study
Summary Charts
October – December 2017

2. Supply Chain Insights LLC Copyright © 2018, p. 2
Agenda
 Study Overview
 Summary
 Analytics Strategies
 Familiarity
 Investment
 Criteria
 Evaluation
 Center of Excellence
 Company Performance

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Respondents Are Split between Users, Vendors, and Other
Types of Professionals

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User Respondents Are Primarily
in the Process and Discrete Industries

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Top Industries Among Users Are Consumer Packaged Goods
and Industrial Manufacturing

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One-Third of Respondents Are Director or Higher and Nearly
Three-Quarters Work in a Supply Chain Role

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Respondents Are Primarily Based in North America or
Western Europe

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Agenda
 Study Overview
 Summary
 Analytics Strategies
 Familiarity
 Investment
 Criteria
 Evaluation
 Center of Excellence
 Company Performance

10. Supply Chain Insights LLC Copyright © 2018, p. 10
Agenda
 Study Overview
 Summary
 Analytics Strategies
 Familiarity
 Investment
 Criteria
 Evaluation
 Center of Excellence
 Company Performance

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All Respondents Were Required to Have Some Familiarity
with Analytics Strategies

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Respondents Are Most Familiar with “Probabilistic
Forecasting” and Least Familiar with “Apache Spark”

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Vendors Are Reportedly More Familiar Than Users with
“Sentiment Analysis,” “Fuzzy Logic,” and “Hadoop”

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Users Claim to Be More Familiar with Nearly All Terms Asked
About Than Vendors Believe Users Are

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Vendors Rate Their Own Familiarity as Notably Higher Than
Their Opinion of Users

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Agenda
 Study Overview
 Summary
 Analytics Strategies
 Familiarity
 Investment
 Criteria
 Evaluation
 Center of Excellence
 Company Performance

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Only 18% of Users Believe Their Company Is Among the First
to Try New Analytics Strategies

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Users Report Highest Adoption Is in Data Visualization

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Vendors Also Report Highest Adoption Is in Data
Visualization

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Vendors Report Higher Investment in Sentiment Analysis and
Data Visualization Than Is Reported by Users

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Users and Vendors Agree That Companies Are Investing
TOO LITTLE in Analytics Strategies

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Top Elements Believed to Be Included in the
Internet of Things Are Preventative Maintenance,
Manufacturing Automation, and VMI

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Top Element Believed to Be Included in Unstructured Data
Mining Is Social Sentiment Data

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Agenda
 Study Overview
 Summary
 Analytics Strategies
 Familiarity
 Investment
 Criteria
 Evaluation
 Center of Excellence
 Company Performance

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Users Report IT and Business Leadership Are Most Likely
Groups to Determine Analytics Investments

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Users and Vendors Agree That IT and Business Leadership
Are Most Likely Groups to Determine Analytics Investment

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Return on Investment and Usability Are Top Criteria When
Selecting Analytics Strategies

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Users Are More Likely Than Vendors to Believe IT Standardization
Is Important When Selecting Analytics Strategies

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Usability, ROI, and Cost Are Among Top Criteria for Users and
Vendors When Selecting Analytics Strategies

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Agenda
 Study Overview
 Summary
 Analytics Strategies
 Familiarity
 Investment
 Criteria
 Evaluation
 Center of Excellence
 Company Performance

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Users Are More Satisfied with Their Analytics Strategies Than
Vendors Believe Them to Be

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While Data Visualization and the Internet of Things Are Seen as
Most Disruptive Today, in Five Years It Will Be Blockchain and
Cognitive Computing

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Overall, Respondents Believe Blockchain, Cognitive Computing,
Software Robots, and Drones Will INCREASE in Level of Disruption

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Data Visualization, Internet of Things, Data Lakes, and
Hadoop Are Expected to DECREASE in Level of Disruption

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Users and Vendors Agree That Data Visualization and the
Internet of Things Are Most Disruptive TODAY

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Vendors Believe the Internet of Things Will Be Most
Disruptive in FIVE YEARS Than Do Users

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What OTHER Analytics Strategies Users Are Excited About

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What OTHER Analytics Strategies Vendors Are Excited About

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What OTHER Analytics Strategies Other Professionals
Are Excited About

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Alignment Between Business & IT and Employee Skill Levels
Are Top Two Challenges with Analytics Strategies

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Users and Vendors Agree on Alignment Between Business
and IT as Among Top Challenges with Analytics

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Users See Management of the Rate of Change as a Bigger
Challenge While Vendors Believe It Is Leadership Support

52. Supply Chain Insights LLC Copyright © 2018, p. 52
Agenda
 Study Overview
 Summary
 Analytics Strategies
 Familiarity
 Investment
 Criteria
 Evaluation
 Center of Excellence
 Company Performance

53. Supply Chain Insights LLC Copyright © 2018, p. 53
One-Quarter of User Companies Have an
Analytics Center of Excellence

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While One-Quarter of User Companies Have an Analytics
Center of Excellence, Most Vendors Believe They Exist

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Vendors Believe the Analytics Center of Excellence
Should Report to Operations or Supply Chain

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Agenda
 Study Overview
 Summary
 Analytics Strategies
 Familiarity
 Investment
 Criteria
 Evaluation
 Center of Excellence
 Company Performance

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Overall, Companies Are Better at Data-Driven Decisions and Data
Access Than Maximizing Analytics Technologies or Testing
Analytical Concepts

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Users Rate Themselves Higher on Analytics Elements Asked
About Than Vendors Rate Users

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Nearly All Users Report Their Company Is Dependent on
Excel Spreadsheets

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Users and Vendors Agree on User Dependence on Excel
Spreadsheets

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About One-Quarter of Users Are Satisfied with Speed of
Getting Data within the Enterprise or within the Network

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One-Fifth of Vendors Believe Users Are Satisfied with the Speed of
Getting Data within the Enterprise, Yet Even Fewer Believe They
Are Satisfied with the Speed within the Network

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Users and Vendors Agree on the Low Level of Satisfaction
with the Speed of Getting Data within the ENTERPRISE

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Users Are More Satisfied with the Speed of Getting Data
within the NETWORK Than Vendors Believe They Are