Rethinking Supply Chain Analytics

Market Insights

01/23/2017

By Lora Cecere

Founder and CEO Supply Chain Insights LLC

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Contents

Research Methodology

Open Content

Disclosure

Executive Overview

Current State

The Future of Analytics

Barriers

Recommendations

Conclusion

Appendix

Other Reports on Analytics

About Supply Chain Insights LLC

About Lora Cecere

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Research Methodology New capabilities from analytics are redefining processes and reshaping supply chain strategies. The

terms are new, and many of the concepts are a radical departure from traditional thinking. In this

report, we share insights from a recent research study that combines both business users’ and

vendors’ (technology providers, consultants, and third-party logistics providers) views.

A study overview is shared in Figure 1, and detailed demographics are outlined in the Appendix.

Figure 1. Study Overview

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Open Content This report is shared using the principles of Open Content research. It is intended for you to read,

share, and use to improve your supply chain decisions. Please share this data freely within your

company and across your industry. All we ask for in return is attribution when you use the materials in

this report. We publish under the Creative Commons License Attribution-Noncommercial-Share Alike

3.0 United States and you will find our citation policy here.

Disclosure Your trust is important to us. In our business, we are open and transparent about our financial

relationships and our research processes; and, we never share the names of respondents or give

attribution to the open comments collected in the research. This research was 100% funded by the

Supply Chain Insights team.

In the development of our research, our philosophy is, “You give to us and we give to you.” As a part

of this philosophy, we share the data, and if interested, our insights, with all the respondents. We are

committed to delivering thought-leading content. It is our goal to be the place where visionaries turn to

gain an understanding of the future of supply chain management.

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Executive Overview Analytic strategies are at the core of digital innovation. It is a building block in digital manufacturing,

autonomous supply chains, and digital path to purchase. New forms of analytics are defining new

capabilities.

Traditional supply chains do not sense. They respond. The response is usually late, and out of step

with the market. Today’s supply chains are dependent on structured data and Excel spreadsheets.

Despite spending 1.7% of revenue on Information Technology (IT), Excel ghettos are scattered

across the organization. Most organizations are held hostage by long and grueling ERP

implementations only to find out at the end of the project that the business users cannot get to the

data.

The traditional supply chain paradigm is an extension to the three-letter acronyms which dominated

the client-server architected world of the 1990s—ERP, APS, PLM, SRM, and CRM—while the more

enlightened business user understands that analytics are not an extension of yesterday’s alphabet

soup.

Historically, analytics has only meant reporting. In contrast, today, analytic strategies are at the core.

As analytics capabilities morph and change, analytics technologies are at the core of the architecture,

sandwiched between the conventional applications and workforce productivity tools as shown in

Figure 2.

Figure 2. Analytic Strategies at the Core of Digital Transformation

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Current State Today, the focus of analytics implementations is on data visualization, unstructured data mining, and

data lake technologies. As will be seen in this report, this is rapidly changing. Within five years, the

most disruptive technologies will be Blockchain and cognitive computing. New forms of analytics will

make many of today’s technology approaches obsolete. Few companies, mainly early adopters, are

working in these areas.

Figure 3. Current Investment Focus for Business Users

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As shown in Figure 4, user satisfaction with the current state of analytics is low. A large opportunity

lies ahead.

Figure 4. Current Satisfaction Rates with Analytics

The Future of Analytics While the levels of investment today in Blockchain and cognitive computing is low, five years from

now these technologies will be major disruptors (see Figure 5). Blockchain will redefine lineage,

supply chain finance, track-and-trace, and visibility, while cognitive computing will redefine workflows,

master data management, decision support, and demand insights. The number of solutions is

endless, but the technologies are not ready for prime time. These capabilities are still only appropriate

for the early adopter willing to invest in co-development.

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Figure 5. Predicting the Future and Analyzing Disruption

Barriers In a digital transformation, teams redefine the atoms and electrons of the supply chain. This includes

process flows, conversion and transport processes, and new capabilities enabled by new forms of

analytics. Imagine a supply chain that senses, learns, and adapts in response to the market, one

where data is available at the pace of business. It is hard to imagine because it is so different from

today's reality.

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Figure 6. Coalescence of Technologies to Drive a Digital Transformation

To imagine a future built on new forms of analytics requires throwing away current paradigms and

learning new techniques. Embracing the possibilities has many challenges. For business leaders, the

greatest issues, as shown in Figure 7, are the alignment between business and IT, employee skill

levels, and management of the rate of change. These issues are not trivial.

Over the last decade, the gaps between business and IT teams grew. The reasons are many.

Contributing factors include business process outsourcing, downsizing, right-sizing, cost-cutting and

baby-boomer retirements. Client-server technologies are quickly becoming legacy. Business leaders

are frustrated with long deployments, and IT leaders are struggling with staffing. Many built strategic

plans believing that consultants could help them with specialty skills, but the market is flooded with

generalists. IT is managed as a cost center, and business leaders are seeking value. Is it any wonder

there is a disconnect?

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Figure 7. The Challenges for Companies Attempting to Implement New Forms of Analytics

The opportunity is high. The pace of change, and the shift of market dynamics, in the last three

decades is unprecedented. Traditionally, the focus on IT was implementation. Today, with the

evolution of cloud-based deployments, the need is configuration and evolution. In short, how can

companies maximize the value of current systems? The pendulum is shifting, requiring business

users to be more fluent in the world of IT, and technologists to have a greater technology

understanding.

It is not easy. Most organizations have downsized IT and line-of-business teams. The result? A

decline in the effectiveness of IT systems implemented over the last decade. Neither team has

excess resources, and the business struggles to speak the language of IT, while the IT resources

quest to know more about the business. Most are at a stalemate.

In this process of moving forward, I am often asked, “How can we deploy new forms of analytics

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without fixing the basics?” The caution is that perhaps new forms of analytics are the answer to fix the

basics. To understand the possibilities, carefully define what "fix the basics" means and start to

brainstorm how new approaches can make a difference.

Next, start to question existing paradigms. The resultant architectures are less dependent on manual

touches and licensed software. They are less ERP-centric.

Build with the goal in mind, and with clear definitions. Focus on the automation of meaningful use

cases that improve business usability and return on investment. Data lakes and clouds offer new

alternatives to reduce costs and improve value.

Figure 8. Criteria Driving Analytic Strategies

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Recommendations In the process of forming an analytics strategy, question existing paradigms.

Question the Role of Enterprise Resource Planning (ERP). In the exploration of new possibilities,

question long, multi-year ERP implementations. The lengthy deployments are an opportunity cost to the

organization. In a digital transformation, the role of ERP shifts to be less central. The ERP system

becomes a system of record for financial transactions however, the role within the supply chain

diminishes. In the digital transformation, ERP is not the system of record for B2B, quality specifications,

or supply chain planning.

Go Fast to Go Slow. Test the possibilities of new technologies. Test and learn through small agile

sprints. Fail forward and invest in learning. Avoid conference room discussions based on slideware, and

work with technology innovators to test and learn. Today, companies struggle to test new approaches

(see Figure 9). Invest in a team of resources to drive process innovation through new forms of

analytics.

Figure 9. Current State of Analytic Strategies

Agile Sprints Require Agile Procurement Processes. While traditional IT projects are based on RFP

selection criteria and long, drawn-out selection criteria, the test-and-learn agile sprint enables the

organization to test-and-learn nimbly. Set the expectation that it is ok to fail.

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At the Beginning of a Project, Shake Hands Affirmatively with Master Data Management. A

common misconception is that a digital transformation needs to start with the cleansing of master data.

Instead, the digital transformation embraces disparate data and leverages machine learning to

harmonize and synchronize data sources. Grab the tiger by the tail. Use "schema-on-read"

technologies and rely on prescriptive, and cognitive, computing to drive insights. The current issues

with master data were largely driven by the focus on transactional systems requiring "schema-on-write"

(fixed data structures/hierarchies).

Rethink the Possible. While the traditional analytical approaches were based on analytics as an add-

on to what I term alphabet soup (ERP, APS, WMS, CRM, SRM, SCE), in a digital transformation

analytics are at the core. While the current focus is on data visualization using descriptive analytics,

slowly the industry is embracing unstructured data and new forms of analytics to redefine decision

support. The goal is to power data-driven processes that move at the speed of business. For most

businesses this is a great opportunity.

Conclusion 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.

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Appendix In this section we share the demographic information of survey respondents, as well as additional

charts referenced in the report to substantiate the findings. The participants in this research answered

the survey of their own free will. There was no exchange of currency to drive an improved response

rate. The primary incentive made to stimulate the response was an offer to share and discuss the

survey results in the form of Open Content research at the end of the study.

The names, both of individual respondents and companies participating, are held in confidence. The

demographics are shared to help the readers of this report gain a better perspective on the results.

The demographics and additional charts are found in Figures A–E.

Figure A. Respondent by Role

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Figure B. Overview of Company Demographics

Figure C. Characteristics of Respondents by Industry

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Figure D. Characteristics of Respondents by Role within the Company

Figure E. Respondent by Role

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Other Reports on Analytics Readers may gain added value by accessing complimentary reports on the Supply Chain Insights

website:

Putting Together the Pieces Supply Chain Analytics, September 2016

Big Data and Analytics, February 2015

The Art of the Possible, February 2013

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About Supply Chain Insights LLC Founded in February 2012 by Lora Cecere, Supply Chain Insights LLC is in its sixth year of operation.

The Company’s mission is to deliver independent, actionable, and objective advice for supply

chain leaders. If you need to know which practices and technologies make the biggest difference to

corporate performance, we want you to turn to us. We are a company dedicated to this research. Our

goal is to help leaders understand supply chain trends, evolving technologies and which metrics

matter.

About Lora Cecere Lora Cecere (twitter ID @lcecere) is the Founder of Supply Chain Insights LLC and

the author of popular enterprise software blog Supply Chain Shaman currently read

by 15,000 supply chain professionals. She also writes as a Linkedin Influencer and

is a a contributor for Forbes. She has written five books. The first book, Bricks

Matter, (co-authored with Charlie Chase) published in 2012. The second book, The

Shaman’s Journal 2014, published in September 2014; the third book, Supply

Chain Metrics That Matter, published in December 2014; the fourth book, The

Shaman’s Journal 2015, published in August 2015, the fifth book, The Shaman’s Journal 2016,

published in June 2016 and the sixth book, The Shaman’s Journal 2017, published in July 2017.

With over 14 years as a research analyst with AMR Research, Altimeter Group, and Gartner

Group and now as the Founder of Supply Chain Insights, Lora understands supply chain. She has

worked with over 600 companies on their supply chain strategy and is a frequent speaker on the

evolution of supply chain processes and technologies. Her research is designed for the early adopter

seeking first mover advantage.