Highlights of Supply Chain Insights’ 2016 Research

12/15/2016 By Lora Cecere

Founder and CEO Supply Chain Insights LLC

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Contents

Research Methodology

Disclosure

Executive Summary

What is Supply Chain Excellence?

What Drives Value?

Building the Customer-Centric Supply Chain

Why is Supply Chain Planning So Hard?

Reflecting on History

Five Reasons Why Supply Chain Planning Is So Hard.

Issue #1 - Governance.

Issue #2 - Strategy: What Defines Supply Chain Excellence?

Issue #3 - Shared Vision: What Is a Good Plan?

Issue #4 - Talent.

Issue #5 - Alignment.

Return on Investment

Improving Supply Chain Reliability

What Is Supplier Development? Diversity?

Program Focus

Change Management and Resistance

Material Management: Production, Raw Materials

and Global Commodity Councils

Emerging World of Supply Chain Analytics

The Steps to Define a Holistic Supply Chain Analytics Strategy

The Role of Analytics in Developing Strategies for Supply Chain 2030

Recommendations

Summary

Primary Research: Reports Used in Compiling This Research in Review Report

About Supply Chain Insights LLC

About Lora Cecere

Endnotes

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Research Methodology We are committed to delivering thought-leading content for the supply chain leader. Our goal is to be

the first place that visionaries turn to gain unique insights to drive supply chain excellence.

This report is a compilation of quantitative research published by Supply Chain Insights during the

period of January through December 2016.

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

relationships. In this research process, we never share the names of respondents and/or give

attribution to open comments collected in the research.

Our philosophy is “You give to us, and we give to you.” We collect data from a private network of

qualified participants and openly share the results. The participants of our research always receive

the final reports; and, if interested, we share insights from the studies with the respondents of our

quantitative surveys and qualitative interviews in a complimentary one-hour phone call with supply

chain teams.

This report is written and shared using the principles of Open Content research. It is intended for you

to read and share freely with your colleagues and through social channels like LinkedIn, Facebook

and Twitter. When you use the report all we ask for in return is attribution. We publish under the

Creative Commons License Attribution-Noncommercial-Share Alike 3.0 United States and our citation

policy is outlined on the Supply Chain Insights Website.

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Executive Summary This report is designed to summarize key findings in 2016 by Supply Chain Insights on supply chain

excellence. During the year we tendered ten quantitative surveys and correlated the research

responses to 15 years of balance sheet analysis of publicly held corporations. We find that over 85%

of supply chains are stuck in driving improvement and outperforming competitors. The primary reason

is traditional thinking. Here we challenge traditional paradigms while offering insights to stimulate new

thinking.

What Is Supply Chain Excellence? No two supply chains are alike. Business requirements are changing quickly while supply chain

processes are evolving slowly. There is a growing gap. Today the average supply chain organization

is 15-years old, and as shown in Figure 1, one out of three companies state there is room for

improvement in supply chain performance.

Figure 1. Descriptors Used by Supply Chain Leaders to Describe Their Supply Chains

While companies desire a supply chain that is aligned, fast, agile, and proactive, this is not the current

state. Instead, today’s operations are controlled, global and reactive. In building today’s supply chain,

increasingly supply chain leaders are learning that the tightly integrated IT infrastructure defined in

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the last two decades is an impediment to creating an agile, proactive and aligned supply chain. In

Figure 2 we contrast the characteristics of the current state of the supply chain with the desired state

by supply chain leaders.

Figure 2. Supply Chain Descriptors: Current State versus Desired Operational Condition

Despite the gaps in overall performance, many supply chain leaders continue to label current

practices as “best practices.” We think this is problematic. Over the year we challenged the status

quo and asked supply chain leaders to rethink the current state.

What made a difference in performance? Five characteristics—executive understanding of supply

chain excellence, supply chain visibility, organizational change management, cross-functional

alignment, and the ability to access and use data—correlate to the “belief” that the supply chain is

working well. The analysis is shown in Figure 3. The numbers in the box show the gap between

companies stating their supply chain is working well, and those who believe their supply chain is not

performing well.

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Figure 3. Characteristics of Companies with Supply Chains Working Well

Alignment and agility improves as companies build strong horizontal processes, i.e. a focus on

revenue management, Sales and Operations Planning (S&OP), new product launch/innovation (NPI),

Corporate Social Responsibility, and Supplier Development. As shown in Figure 4, in the most

successful companies these horizontal processes are interlinked and stretch from the customer’s

customer to the suppliers’ supplier. We find that a functional or project-based orientation does not

drive an equal level of value.

Figure 4. Definition of Horizontal Processes

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Today the strongest S&OP, NPI, and supplier development processes are in the discrete industries.

The gap in performance of horizontal process definition effectiveness between process-based and

discrete industries has widened between the industries in the period of 2006-2015. We feel this is one

of the reasons many process-based companies are regressing in the Supply Chain Metrics That

Matter™ analysis.

Across our studies we find the occurrence and satisfaction of these horizontal processes vary. These

are shown in Table 1.

Table 1. Current State of Horizontal Processes

What Drives Value? To build on this initial research we wanted to take it one step further and answer the question of what

drives value. In the analysis of companies for the Supply Chains to Admire, we use Price to Tangible

Book Value (PTBV) as the proxy metric of value. We believe that improving the value of shares

outstanding in relationship to assets, investments and capital strategies (tangible book value) is within

the control of the supply chain leader. The definition of PTBV is:

Price to Tangible Book Value = Market Share Price / Tangible Book Value/Share Outstanding

To gain insights on the relationship between supply chain decision making and value, we used our

survey database to understand the relationship between strategies and process options, and the

impact on improving PTBV. To complete this analysis, we analyzed the data collected in 28

quantitative studies over the period of 2012 to 2015. This included 2,147 respondents from

manufacturing, retailing, distribution and third-party logistics companies.

Through this analysis we find that companies who have a successful Supply Chain Center of

Excellence, an S&OP process that is considered to be effective, and have less business pain with

supplier reliability, are more likely to be driving PTBV performance.

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Figure 5. Drivers of Price to Tangible Book Value

Building the Customer-Centric Supply Chain As growth slows, manufacturing companies struggle with rising complexity and increasing levels of

demand error. The question is “Could companies decrease complexity and improve growth by

building outside-in processes that are customer-centric?” We believe the answer to this question is a

resounding “YES!” However, there is a problem. Across the industry there is no common definition of

customer-centric supply chains. In addition, there is no clear and accepted methodology to build this

core competency. As a result, most companies have forged their own paths.

In this study, 80% of the respondents have a customer-centric strategy; yet, only 46% of companies

state that they have built a customer-centric supply chain. Companies struggle to drive alignment and

build constancy of purpose.

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Figure 6. Current State of Customer-Centric Supply Chains

Today 46% of respondents rate their supply chain as performing well on the delivery of a customer-

centric supply chain strategy. The definition of a customer-centric supply chain used for this research

is: one that is aligned with order management, product strategies and distribution processes to

deliver/adapt to against customer segmentation strategies.

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Delivering on the promise of a customer-centric supply chain is not easy. One of the largest issues is

understanding what customers really value. Some of the issues include:

Table 2. Verbatim Responses to Why Supply Chain Is or Is Not “Customer-Centric”

Gaining alignment across the supply chain to serve the customer is the goal. When companies look

at what is important versus current performance, the gaps become clear as shown in Figure 7. The

reason why? Most of the historic focus was on distribution-centric processes: examples include

scorecards, vendor managed inventory, and collaborative planning. Companies do these well, but

they do not drive the required change. The tougher and more important tactics include the

implementation of meaningful cost-to-serve policies, management of complexity, and driving

customer segmentation into Available to Promise (ATP) and order policies. Closing these gaps

requires strong cross-functional alignment with sales and a clear understanding of what the customer

values. Both are an issue in most organizations.

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Figure 7. Customer-Centric Policies: Performance versus Importance

Many companies bandy about words like customer-centric in strategy discussions, but fail to define

the term to make it actionable. Many confuse demand-driven, customer-centric, and outside-in

processes; these are three separate, but intersecting, strategies. Getting clear on the terms and

strategies is a first step. In Figure 8, we share the overlaps.

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Figure 8. Customer-Centric Supply Chain Definition

The average respondent in this study had a customer-centric supply chain strategy for their primary

customer over five years; yet, 54% report their supply chain is not working well. Our takeaway?

Should they feel so good about their progress? We think not. Success is easier said than done.

There are many pitfalls. Here we discuss three:

Pitfall #1: Being Customer-Centric Does Not Mean Doing Whatever the Customer Wants. Let’s

consider the story of two clients in Houston. The companies were fierce competitors. Each distributor

delivered oil and gas products to refineries. The companies were commodity-based businesses and

operated on razor-thin margins. One company defined the customer-centric strategy as, "Do

whatever the customer wants." Their costs were higher and their reliability to the customer was

lower. The organization was always jumping through hoops. The second organization had a very

different definition of customer-centric. Their vision was to manage distribution policies based on

customer segmentation with a focus on reliability. At the second company, policies were clear and the

focus was on reliable delivery. At the end of the year we watched both companies gather in a room

for the most valued supplier award. The company that constantly jumped through hoops did not win

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the award, while the second company won the Supplier of the Year. What can we learn? When it

comes to customer-centric supply chain strategies, reliability matters. Failed promises, no matter how

well-intended, have long-term consequences.

Pitfall #2: Getting Clear on the Customer. Most companies have multiple customers. In this study,

the average manufacturer served three customer types. These relationships form a value network

within the channel. The key is to identify the primary customer and gain clarity on what is valued, and

then align the organization against what is important. For example, while the healthcare industry has

historically seen the doctor as their primary customer, the power is shifting to health and wellness.

This does not mean the doctor is unimportant. Instead, it is about managing multiple parties in the

value chain, including the patient.

Pitfall #3: Segmentation and the Management of Complexity. In Figure 9 we show the gaps in

the execution of customer-centric policies and strategies. The top three gaps are: visibility of channel

inventories and orders; management of complexity; and the alignment between commercial and

operations teams. These three characteristics often go hand-in-hand. When there is close alignment

there is usually better management of complexity and the sharing of channel data.

Figure 9. Gaps in Customer-Centric Strategies

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The average company uses five practices to execute a customer-centric supply chain. The details are

shared in Figure 10.

Figure 10. Customer-Centric Policies Deployed

The issue is that the strategies deployed do not resolve the gaps. While there is a focus on

scorecards and distribution strategies, companies struggle to align on customer-centric policies. To

drive true value, sales and operations must align and manage customer and product complexity.

There are many gaps in the execution of customer-centric strategies. The implementation of channel

visibility solutions is very low (16%). The lack of use of channel data and customer sentiment data is

one of the reasons why most companies feel their supply chains are underperforming, despite the

availability of data.

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Why Is Supply Chain Planning So Hard? Supply chain processes are evolving. Supply chain processes are young compared to those of more

established functions like sales, finance and marketing. As a result, in many organizations supply

chain planning is not well-understood.

Figure 11. Overview of Supply Chain Maturity

Supply chain planning technologies evolved in the late 1980’s to improve enterprise decision making.

Using specially designed analytics, the technologies help companies to forecast demand, and plan

supply. The selection and implementation of specific supply chain planning technologies needs to be

designed with the goal in mind.

While consultants promise that “an 80% solution is good enough,” we seldom find this to be the case.

The selection and implementation of supply chain planning technologies is fraught with issues. The

goal of this report is to improve a company’s odds for success in driving value in supply chain

planning processes.

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Reflecting on History Supply chain process evolution is now 35 years old, but the development and the adoption of supply

chain planning processes is newer. The use of the technologies is a new way of doing business.

The concepts gained mainstream adoption in 1995. Late in the 1990s the technologies were

overhyped and the benefits over-promised. As a result, the supply chain planning technology market

contracted with massive consolidation. In this period over 75% of the companies in the supply chain

planning technology market were acquired. Those company names are now history.

The original definition of planning was limited by the possibilities of 32-bit architectures using client-

server technologies. The data models were limiting. Today, with the evolution of concurrent

optimization and cloud-based deployments, more is possible. Over the past two decades within the

software industry, the mathematical models, capabilities for employee collaboration, and visualization

capabilities improved.

In this period much changed within the supply chain organization. Regional teams became global.

Supply chain groups were formed. The first- and second-generation supply chain pioneers retired.

Mergers and acquisitions reigned. As a result, many supply chain organizations reorganized and re-

formed. In the past five years we tracked these overarching trends:

Functional to Enterprise Processes. The initial focus was on improving functional excellence.

There was a singular focus on sourcing, manufacturing and logistics. Over time they evolved

into enterprise processes like Sales & Operations Planning and Revenue Management.i

Functional and enterprise processes are both important and need to be built together in a

holistic plan.

Outsourcing. Outsourcing increased, giving importance to the management of value networks

to better manage outsourced manufacturing and transportation. The use of Electronic Document

Interchange and Fax-to-EDI morphed to include networks designed for one-to-many and many-

to-many bidirectional flows.ii Organizations are just now beginning to develop planning for multi-

tier relationships. Most of the focus, up until now, has been on supply chain planning within the

four walls of the enterprise.

Design of Networks. While 5% of companies designed their networks two decades ago, today

two-thirds of companies use network design technologies.iii The evolution of supply chain design

capabilities evolves slowly. We show the normal path in the maturity framework in Figure 12.

Design processes mature from ad hoc to systemic and ongoing analysis, and from a functional

view to a holistic system view.

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Figure 12. Network Design Maturity Model

Maturity of Inventory Optimization Technologies. In the last decade inventory optimization

technologies improved—both in breadth and depth—to accelerate financial balance sheet

results.iv The use of these multi-tier inventory solutions improved inventory decision making and

significantly improved inventory turns in mature implementations. In Figure 13 we share this

impact.

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Figure 13. Advancement of Inventory Optimization Technologies

Evolution of Demand Sensing. While traditional forecasting predicts demand in a longer-term

or tactical timeframe, in 2003 pattern recognition evolved to sense demand patterns in the short-

term duration. This technology is slowing being adopted. Today there are 25 companies in

various degrees of implementation of demand sensing technologies.

Technology capabilities in planning technologies evolved faster than the work processes. As a result,

in our work companies ask many questions:

Do companies drive higher levels of results when the solutions are sourced from the same

vendor?

How do I select a technology? Improve the value proposition through implementation?

How many planners are needed? How does the number of planners vary by company size and

number of items?

Technologies have evolved. When should I switch out my current solution for a new approach?

How should the planners be organized to maximize value? What should the career path look

like?

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Most companies struggle with planning implementations. This is especially true if the project is

executed through a typical technology approach. While the technology can be quickly bolted into IT

architecture, building planning capabilities within the organization takes time and perseverance.

There are many pitfalls. Let’s start the discussion with the five reasons why driving success in supply

chain planning implementations is so hard.

Five Reasons Why Supply Chain Planning Is So Hard. Listed below are the barriers we see in our work with organizations attempting to create an effective

supply chain planning organization:

Issue #1 - Governance Supply chain planning tools are designed to improve organizational decision making. The use of

planning technologies is simpler when deployed within a function of a regional organization. Why?

The goals are clear, and the alignment of functions is less of an issue.

As companies grow larger, global governance is less clear. It becomes a problem. Simply put, it is

difficult to have better tools to make a decision if companies have not thought about the best way to

make a decision. Before the implementation of supply chain planning technologies, getting to data

and reviewing decision options is hard. After the implementation, data is more available and there is

greater visibility within the organization of the implications of a decision. What is possible after the

technology implementation is vastly different than beforehand. As a result it is important to start the

project by asking the question, “How should the company make decisions?”

The most successful companies tackle these issues proactively. For most it is an opportunity. Within

an organization there is tension as companies attempt to answer the questions of:

How should the company make decisions and planning trade-offs?

What is the role of business groups and regional teams in the use of new technologies to improve

planning?

Which decisions should be made globally? Regionally? Locally? How should these teams

coordinate work?

How do we make the best decisions possible in a global organization?

What level of risk is the company willing to take?

How should the company orchestrate cross-functional trade-offs?

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One in two companies with revenues greater than $5 billion have a supply chain center of excellence,

and the majority of the companies with a center of excellence also actively work on the design of the

supply chain. As can be seen in Figure 14, most companies have a centralized Center of Excellence

(COE), but focus on serving the regions and divisions. Planning is only managed globally in 17% of

the organizations.

Figure 14. Supply Chain Governance

The discussion of local versus global, and divisional versus corporate, planning is an important

decision that evolves over time. Initially, due to labor constraints, many companies implement

technologies with a focus on corporate planning. However, as the organization understands and

embraces planning, the governance will often shift to regional and divisional teams. The key is

making it a conscious choice and making sure that the work teams understand roles and

responsibilities.

An important question to ask is “Where do we make the pivot in supply chain processes?” This

defines where companies should pivot between local and global processes to maximize asset

utilization. The most frequent organizational pivot defines supply chain groups in commercial

organizations as local or regional and supply chain groups in procurement. Here is the logic:

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Procurement. The procurement group is often global to have “one face to the supplier” to gain

aggregate buying power. Mature organizations orchestrate aggregate buying strategies based on

demand and supply probabilities.

Logistics. Logistics planning varies based on scope and scale. If the company is an international

shipper with a focus on air, ocean, and long haul over-the-road, the logistics team is normally

managed globally. In contrast, last-mile delivery is typically managed locally.

Manufacturing. Manufacturing strategies are based on the global product platform. If the products

are shipped across divisions in a matrixed organization, the manufacturing organization is usually

planned globally in the tactical horizon, locally at the plant level. In contrast, if the manufacturing is

regional, manufacturing planning is typically local or regional.

Customer Service. If customers are local, customer service will usually be local; however, if

customers are national or global accounts, customer service can be regional or global.

Commercial Teams. Commercial teams with supply chain support groups are typically regional.

Plan. Design and tactical planning teams will follow the functional flow design/pivot while

operational and executional deployments will follow the regional design flows.

The key is to ensure the company knows how to make a decision and who is driving the decision.

While the technologies ensure that decision making is quicker and more holistic, clarifying roles helps

companies to maximize the value.

Issue #2 - Strategy: What Defines Supply Chain Excellence? The basic assumption of supply chain planning, and of optimization, is to improve an objective

function. To drive results the desired outcome must be clear.

This is easier said than done. Supply chains are complex. The management of metrics and business

results is fraught with political issues. Most organizations do not understand the relationships

between supply chain metrics like operating margin, growth, inventory turns and Return on Invested

Capital (ROIC). They are tightly interconnected, forming an Effective Frontier of potential outcomes.

When thinking through the Effective Frontier, as shown in Figure 15, supply chain metrics need to be

defined as a portfolio. There are finite trade-offs between costs, inventory, and asset utilization

strategies. The objective function, or outcome of the planning system, should maximize the potential

of the Effective Frontier. The outcome should be feasible. To set realistic targets may require

modeling using network design tools in advance of a planning implementation to understand and

apply the insights of the metrics trade-offs.

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Figure 15. The Supply Chain Effective Frontier

In the process, a mistake many organizations make is thinking there are “best practices” which can

be widely adopted across companies. Instead, each supply chain planning road map needs to be built

with the company’s goals and with strategies in mind. What will work in the culture of one company

may not be a good fit in another.

Supply chain planning is also industry specific. While there are some common principles, supply

chain planning needs to be designed with the goal in mind. Supply chain strategy defines the goal,

and the supply chain strategy needs to align with the business strategy. In Figure 16 we share a

useful framework to define supply chain strategy.

Figure 16. Use of Supply Chain Planning in the Context of Supply Chain Strategy

The supply chain is a complex system with increasing complexity. Only after the definition of the

strategy should companies define business processes. A common mistake is defining processes first.

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When this happens, companies will often try to automate past practices, or believed best practices,

with planning technologies without embracing what is possible through advanced analytics.

Planning technologies should enable a step change of process improvement. They should never be

used to automate past practices; instead, the thinking should be about the definition of outside-in

processes, based on channel and supplier relationships, to sense and respond.

In summary, supply chain excellence must be defined. It cannot be assumed. The definition varies by

company. Too few companies take the time to define it before implementing supply chain planning.

As a result, the wrong decision processes are accelerated. In the words of one of our clients, “A bad

planning project is like making bad decisions on steroids.”

Delivering on supply chain excellence goals also does not happen by just creating a Supply Chain

Center of Excellence. While one in three companies have a supply chain center of excellence, few

have agreement internally on what defines supply chain excellence. This is one of the primary

reasons that one out of two supply chain centers of excellence fail. In many companies, frustration

abounds.

As seen in Figure 17, supply chain planning is one of the primary roles of the Supply Chain Center of

Excellence. If this group is not clear on the definition of what drives excellence, it is tough to get the

project going on the right path.

Figure 17. The Role of Supply Chain Centers of Excellence in Defining Supply Chain Planning

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Issue #3 - Shared Vision: What Is a Good Plan? Supply chain planning means different things to different people. It is a multifaceted project for both

demand and supply. There is a focus across four time horizons: strategic planning (a longer time

duration of months and years); tactical planning (a medium time duration of months with planning

represented in weeks); operational planning time horizons (a shorter time duration with planning

focused in days with output in days and hours); and executional planning (near-term planning of 0-

two days with output in minutes and hours). The tactical duration of planning is usually 8-16 months

while the operational time horizons are 0-16 weeks. Operational planning tends to be functional in

orientation: production planning, transportation management, and material requirements. Executional

planning, allocation and Available-to-Promise (ATP), tends to be more rule based. Companies that

excel in planning have a clear road map for both demand and supply across the time horizons.

It is not simple. Most companies have two to three instances of demand and supply. As shown in

Figure 18 more than 75% of companies have demand and supply implementations, but in companies

greater than $5 billion in revenue you can often have only demand.

Figure 18. Demand and Supply Planning Instances

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In our planning benchmarking efforts we studied the maturity of companies on demand and supply

planning. In Figure 19 we share a sample of one company’s maturity in the areas of planning. (This

type of framework is useful to plot planning maturity, and evaluate enterprise and network planning

technology decisions.) This company is typical. They have implemented numerous Enterprise

Resource Planning technologies, and focused on transactional efficiency, but not cracked the code in

making planning effective.

The organization is rife with change management issues. They implemented supply chain planning as

a technology project and never matured the organization’s capabilities to use decision support

technologies. The planning tools purchased were implemented within functions without a holistic road

map.

Supply chain planning is future looking. It is about the feasibility of the plan. A good planning process

helps teams to see new possibilities and minimize risks. The tools have “what-if” capabilities and are

used by the planners. (In our research we find that only 30% of companies have sufficient “what-if”

capabilities.)

Figure 19. A Supply Chain Planning Maturity Assessment

Dark Green represents mature capabilities, where a company is above the peer group; light green

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represents average capabilities; and blue represents planning maturity below the peer group. Most

process companies are more mature in transportation planning, while discrete companies are more

mature in materials planning. Maturity in manufacturing and inventory planning is a characteristic of a

mature supply chain planning implementation.

To drive planning maturity, it is important to think about plan consumption (synchronization) between

and amongst the planning layers—strategic, tactical, operational, and executional—and the relative

maturity between planning in sell, deliver, make, and buy, and the ability to orchestrate decisions

cross-functionally. It requires a holistic view.

In our research we studied what drove a higher rate of success in supply chain planning for business

users.v The elements in red within Table 3 represent a statistically significant difference at a 90%

confidence level between respondents who rate themselves as more satisfied than those who are

less satisfied. In general, companies that implement best-of-breed solutions using their technology

provider for implementation are more satisfied than companies who implement supply chain planning

extensions of Enterprise Resource Planning (ERP) or use a third-party consultant.

Table 3. Characteristics of Highly Satisfied Companies with Supply Chain Planning

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As can be seen from the study, when this happens, the rate of implementation is faster and the time

for ROI quicker.

In assessing planning maturity, trust issues abound. Companies do not trust black boxes. One of the

characteristics of maturity is when planners use the system to plan. A sign of a lack of maturity is a

strong dependency on Excel spreadsheets. Other characteristics of a good plan are:

Feasible Plan. The solution should adequately model the business, including constraints and

floating bottlenecks. To understand the capabilities of the technologies, they need to be tested

and tuned in conference room pilots prior to implementation.

“What-If” Capabilities. Only 30% of companies have sufficient “what-if” capabilities in their

planning. The goal of the decision support platform is to see the consequence of multiple

scenarios.

Timeliness of the Plan. Scalability is a major factor. The frequency and granularity of the plan

needs to match the cadence of the business. Test for scalability prior to implementation.

Issue #4 - Talent The first and second generations of supply chain pioneers are retiring, and as a result there is a

supply chain talent gap in middle management as shown in Figure 20. While there are many talented

candidates coming from supply chain programs, the challenge is training and onboarding them fast

enough to meet supply chain planning needs. The toughest positions in supply chain within this

middle management skills gap are in the area of supply chain planning.

Figure 20. Mid-Management Skills Gap

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As shown in Figure 21, some of the greatest issues in the supply chain skills gap are in the areas of

demand, supply, and Sales and Operations Planning. Positions requiring both a deep business

process understanding, and analytics capabilities, are hard to fill. As a result, companies need to train

their teams and ensure the evolution of a career path to achieve adequate training and retention. Due

to the market shortage, the pressure on supply chain planning talent is high; and as a result, the time

to replace a planner through external recruiting can be seven to nine months.

Figure 21. Challenge of Filling Supply Chain Positions

Issue #5 - Alignment. When business teams are aligned, the satisfaction with supply chain planning is higher. The

unfortunate reality is that the teams are not aligned, with the greatest gaps (as shown in Figure 22)

happening between commercial and operational teams. When companies can close the alignment

gaps there is greater agility and progress on cross-functional metrics.

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Figure 22. Organizational Alignment

In our research we find it is easier to drive alignment in smaller organizations, and driving alignment

in larger organizations is tougher. This can happen through cross-functional incentives and

leadership, but improving alignment is a prerequisite for satisfaction with supply chain planning.

Successful supply chain planning implementations happen within organizations with tighter, more

aligned teams. Gaining alignment between commercial and operations teams is “job one” for the

Chief Operating Officer trying to drive success in supply chain planning.

Return on Investment Despite the issues and barriers, in our quantitative survey of 184 planning instances, the average

implementation has a Return on Investment (ROI) for supply chain planning of nine months. In the

larger world of technology implementations, a less than one year ROI has great appeal. Only 35% of

the projects are over budget, and 66% of companies were satisfied with their planning solutions. The

results of the study are shown in Figure 23.

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Figure 23. The Return on Investment with Supply Chain Planning

Improving Supply Chain Reliability Trust, but verify. During the recession of 2007, trust in the extended supply chain was broken. As

companies throttled back production to adjust to falling demand, many suppliers who thought they

were strategic were left “holding the bag.” Risk was pushed backwards in the supply chain, violating

the tenets of many strategic relationships.

As a result shipments were refused and orders canceled. Payments were delayed and trust was

violated. Many supplier companies never recovered, tightening the supply of materials in discrete

value chains like automotive and high-tech.

As growth slowed over five years, the supply chain focused on an agenda to reduce costs.

Commodity price volatility increased and procurement pressures to reduce costs resulted in

transactional buying (a focus to minimize price variance). In many companies, strategic sourcing and

commodity management through category buying programs took a “back seat.” Supplier programs

become more reactive.

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In this environment, as shown in Figure 24, supplier viability—an environment for a supplier to

manage a successful business—became a pressing risk issue. Sitting four and five levels back in the

value network, suppliers experienced a double-whammy: pressure to reduce price along with the

lengthening of Days of Payables.

Figure 24. Supply Chain Risk Management Comparison for the Period of 2010 to 2020

Ironically, while technology in supply chain finance progressively improved to enable a quick transfer

of funds across industries, Days of Payables increased 30 and 60 days. The second irony is the cost

of capital. While brand owners have a lower cost of capital than their suppliers, few companies extend

their brand capabilities in supply chain finance to their suppliers. While companies talk supply chain

finance, squeezing suppliers is the market reality.

In parallel, economic uncertainty and demand volatility increased, also putting pressure on the

supplier base. While the adoption of demand-driven processes could improve supplier alignment,

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demand-driven process adoption is slow. Few companies are taking ownership of demand signals to

their supply base.

Traditional processes dominate. Companies are strongly wedded to supply-centric processes based

on traditional forecasting processes using order patterns. With the lengthening of order latency, and

the lengthening of the long tail of the supply chain, the synchronization of suppliers into the value

network is out of step, creating waste and obsolescence.

The synchronization issues are greater with the increase in supply chain complexity.

To improve supplier viability, supply chain leaders recognize they need to take responsibility for

supplier relationships in the management of strategic supply. For many, the evolution of “supplier

development” programs to design long-term win/win relationships is relatively new. The supplier

development team is a group designed to help suppliers achieve supply chain objectives. Supplier

development is so new that today many supply chain leaders are unaware of the term.

What Is Supplier Development? Diversity? When asked what defines an excellent supplier development program, companies define it as one

which is collaborative and performance-driven. The program has strong accountabilities on both buy-

and sell-side relationships.

The terms ‘supplier diversity’ and ‘supplier development’ are often bandied about and used at

conferences in the same sentence, but they are very different programs. While supplier development

is focused on improving supplier viability and the reliability of supply, supplier diversity is focused on

improving the percentage and contribution of women-owned and minority-managed suppliers. As

shown in Figure 25, the occurrence of supplier diversity programs is more common than the presence

of supplier development programs. Supplier diversity programs are strongly rooted in compliance,

while supplier development programs are more focused on driving opportunity and improving

reliability. In this study, 31% of respondents had both supplier diversity and supplier development

programs.

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Figure 25. Presence of Supplier Diversity and Supplier Development Programs

Supplier development is one of the five important horizontal processes to drive supply chain

excellence against a business strategy. For those with a mature supplier development program, there

is a tight link between these horizontal processes. Today, based on study results, the primary focus is

on process improvement.

Program Focus The program focuses for both buyers and suppliers, as shown in Figures 26 and 27, are on process

improvement and Kaizen events. To our surprise, in this study there is less emphasis on improving

electronic B2B capabilities than we expected. Most of the programs are based on email and

spreadsheets. Today supplier development processes are largely manual.

Scorecards are an important element of the supplier development relationship, with 71% of buyers

using scorecards and 55% of those with scorecards believing they are effective. As with most

programs, you get what you measure. As shown in Figure 26, most of the focus is on quality and on-

time delivery. E-commerce capabilities and electronic sharing of Advanced Shipping Notifications

(ASNs) are measured in less of 20% of the relationships.

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Figure 26. Scorecard Measurements by Buyers

Figure 27. Elements of the Supplier Development Program: Perceived Effectiveness by Buyers

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The scorecards are aligned to drive process reliability. As shown in Figure 27, buyers are attempting

to drive process improvement in reliability. Kaizen events, a part of mature Lean programs, are

considered effective. Electronic commerce is less of a priority, and many companies struggle to

achieve a consistent definition of supply chain excellence which is actionable in a supplier

development program.

Figure 27. Elements of the Supplier Development Program: Perceived Effectiveness by Suppliers

Change Management and Resistance While most companies recognize that supplier development is the right thing to do, there are many

obstacles. The internal politics and obstacles for buyers and suppliers are outlined in Figure 28. As

the pressure increases to reduce costs, the resistance gets higher. Surprisingly, suppliers get more

resistance than the buyers. Legacy supplier relationships, along with executive understanding of

performance metrics, are major stumbling blocks.

Enlightened procurement leaders align with finance. They influence the financial team to understand

the implications of risk, quality, and reliability of supply without a strong supplier development

program, and use this influence to drive the program within the organization.

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Figure 28. Internal Resistance to Supplier Development Programs for Buyers and Suppliers

Figure 29. Internal Alignment in Response to Supplier Development Programs

Education is key. The mature procurement teams help finance to understand the implications of

lengthening Days of Payables, and effectively managing procurement policy and execution through

digital Procure-to-Pay processes. For many organizations, as shown in Figure 29, this is a fight.

The lack of alignment between finance and procurement is a gating factor to drive improvement in

supplier development programs.

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Material Management: Production, Raw Materials, and Global Commodity Councils Growth in global markets is slowing. Stock markets reward growth, and most supply chain leaders

want to be successful in driving a growth agenda. Within the supply chain there needs to be a healthy

intersection of the worlds of gray and black.

In the launch of new products, most companies have a stage-gate process. In this series of

evaluations of what should progress in the new product pipeline, over time, more and more people

get involved in decisions. This is the circle of life for new product launch. This is a world of gray. As

supply chain teams work with new product launch, they must effectively dance with the world of gray.

Why gray? Product specifications are not final. There is no item code, and it is not clear where

products will be produced. Instead, the product is a fuzzy concept gaining definition. The most

important planning processes for the supply chain leader take place in this world of gray. In stage-

gate finalization, traditional planning techniques are not effective.

Most supply chain leaders come from the world of black and white. In operations there is little gray.

Products are made at specification targets, and quality of design is carefully measured through Six

Sigma processes. Process variation is rigorously controlled. Enterprise Resource Planning (ERP)

systems strengthen the discipline of these processes. Within this world there are fixed and well-

defined item codes, production locations, and material specification. This gives rise to a question:

"How will companies grow if they only automate the world of black and don't embrace the world of

gray?" Which leads me to another question, "Are supply chain leaders hampering product

development efforts by forcing black and white process definitions too early onto product launch

processes?" I think so. For example, when we evaluated discrete supply chain capabilities, we see

that respondents in discrete industries rate the performance of technology as effective in evaluating

price, lead times and delivery reliability (this is the world of black and white). In contrast, they rate

current capabilities as less effective in determining financial viability and innovation (the world of

gray). Organizations are currently using Materials Requirements Planning (MRP) from Enterprise

Resource Planning (ERP) solutions, along with Excel spreadsheets; and, as a result, are unable to

collaborate with suppliers to compare design requirements, tolerances and discuss options.

New technology options for collaborative sourcing enable these capabilities.

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Figure 30. Performance of the Most Valuable Technologies in Evaluating Direct Materials Sourcing

Figure 31. Lack of Capabilities within Discrete Industries to Manage Suppliers to Drive Innovation

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In evaluating the effectiveness of supply chain processes in supporting stage-gate processes in

discrete industries—including make-to-order and assemble-to-order processes—based on design

drawing and assembly, we find that companies are satisfied with current material requirements

planning (MRP) and product life cycle management (PLM) technologies, but that each of these is only

effective within a functional silo. This gap is shown in Figure 31. MRP works well within sourcing of

known products (the world of black) and PLM is effective in product design (the world of gray). We

find 98% of companies lack a collaborative technology to bridge across the worlds of black and gray.

As a result, they cannot effectively work with potential suppliers in the fine-tuning of quality of design,

and translating it to quality of conformance. Last week I spoke on a panel on value-added

engineering. As the discussion progressed what became clear is the current focus is on cost

management in procurement, and on product launch in engineering. The processes to engage

suppliers on innovation, and improvement of value-based engineering are a lost opportunity.

Emerging World of Supply Chain Analytics Supply chains are drowning in data, but are low on insights. While the cost of computing memory was

once a barrier to executing an analytics strategy, this is no longer the case. The largest barrier is the

understanding of new forms of analytics.

Historically, the term supply chain analytics was used to describe reporting. This is no longer the

case. Today there are more options and capabilities for supply chain analytics. There is a proliferation

of new technologies flooding the market.

Ironically, despite the explosion of options, as shown in Figure 32 the supply chain operating team is

more conservative. It is a skewed distribution. When it comes to decision support, the number of late

adopters outnumbers the early adopters three to one. The lack of early adopters, the rapid rate of

change, and the conventional architectural definitions (primarily focused on Enterprise Resource

Planning or ERP-based architectures) are barriers to the adoption of new forms of supply chain

analytics. Driving change requires education, testing and experimentation.

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Figure 32. Risk Profile of Companies Adopting Decision Support Analytics

The Steps to Define a Holistic Supply Chain Analytics Strategy Supply chain analytics requires defining a layer to lie between operational applications—Advanced

Planning, Enterprise Resource Planning, Product Life Cycle Management (PLM), Supplier

Relationship Manager, Supply Chain Execution (SCE), Transportation Management Solutions, and

Warehouse Management Solutions—and workforce productivity technologies like search engines

such as Firefox, Chrome, and Internet Explorer/Edge, and collaborative applications like Yammer and

Socialcast, and Microsoft Office technologies like Word, Excel, and Access. Traditionally the focus of

supply chain leaders was on functional/operational technologies. As a result, there has not been a

holistic focus like the one which is outlined in Figure 33.

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Figure 33. Defining a Holistic Analytics Framework

To define this holistic analytics strategy, start by defining the problem to be answered. Then sort

through the alternatives. This section is designed to be a guide:

A) What Data Types Are Needed to Answer the Problem? When solving business problems and

driving new insights, the first question to ask is “Which data set is required to yield the greatest

insights?” Data comes in two types: structured and unstructured data. Most of the automation in the

supply chain today is based on structured data. (Structured data fits well into rows and columns.

Examples of structured data include transactional and planning data.) Unstructured data does not fit

into relational tables. These unstructured data sets include, but are not limited to, data types like

social sentiment, call-center data, commercial drawings, contracts/partner agreements, maps,

ratings/review data, pictures, warranty information, and weather data.

1. Structured Data. If the data is structured, build analytics on top of relational databases like

Microsoft, Oracle, SAP HANA and Teradata.

2. Unstructured Data. If the data is unstructured then the system requires the use of

nonrelational database open source code through Cassandra, Cloudera, and MongoDB.

B) How Fast and When Does the Data Need to Move? (Not All Data Needs to Move at the Same

Rate or First Class.) What Are the Required Data Structures? The second step in the definition

of data infrastructure starts with mapping data flows. Some questions are, “Where does data need

to pool into lakes for discovery? When does data need to stream in real-time, based on sensor data

outputs?” While streaming data needs to move in real-time flows, most data in the enterprise can

move at a slower rate to support batch processes. Columnar database structures help to move

transactional, and frequently used data, more quickly. (Columnar architectures like SAP HANA

brings frequently used data, based on columns, into memory). However, columnar database

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structures do not work as well for hierarchical and time-phased data architectures of supply chain

planning. Here are some details:

1. Streaming Data Architectures. Stream processing is designed to analyze and act to drive

real-time “continuous queries” (i.e. SQL-type queries that operate over time and buffer

windows). Streaming data analytics are defined by the ability to continuously calculate

mathematical or statistical analytics, on the fly, within the stream. These streaming-data

processing solutions are designed to handle high volume, in real-time, with scalable, highly

available and fault-tolerant architectures. This enables the analysis of data in motion. This is

in contrast to the traditional database model where data is first stored and indexed with

subsequent query processing. Stream processing takes the inbound data while it is in flight,

as it moves through the server. Stream processing also connects to external data sources,

enabling applications to incorporate selected data into the application flow, or to update an

external database with processed information. There is no standard definition of streaming

data architectures for supply chain. These architectures are evolving. The most advanced

companies are using the open source code defined by Apache Spark.

2. Data Lakes. A data lake is a storage repository holding large amounts of raw data in a

native format—structured, semi-structured and unstructured data. The data is formatted

when called for use, and is formatted for analytics/visualization based on business

requirements. Data lakes are primarily used in supply chain for discovery and insights on

commercial, quality or supplier data. Nonrelational database technologies based on Hadoop

are being used for discovery on structured and unstructured data.

3. Data Warehouse. A data warehouse is used to normalize, harmonize and structure data for

reuse and enrichment. The most common use case is harmonization and synchronization of

structural data.

4. Hierarchical Data Structures. The organization of data into a one-to-many

representation/schema for analysis. In supply chain, the most common use of hierarchical

data structures is for forecasting and demand management.

5. Transactional Data Formats. Transactions, or small events, are recorded into relational

database structures. Relational data structures in Enterprise Resource Planning are

architectures designed to record and retrieve business transactions within the organization

to a common system of record.

6. Time-Phased Data Structures. These data structures format over time for analysis. Time-

phased data is the basis of supply chain planning. In the design of supply chain planning,

the focus is on the reuse of rows. In contrast, the management of transactional data is more

focused on column reuse.

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C) What Is Required to Improve Insights? Which Types of Intelligence/Data Models Yield the

Best Results? The goal is to drive insights by adding intelligence to better understand data

patterns. The progression of supply chain analytics moves through four steps. While descriptive

analytics enables the visualization of data, predictive, prescriptive and cognitive analytics brings

progressive use of optimization and machine learning to drive insights from data. These

technologies are packaged into engines requiring data inputs, data model definitions and data

outputs. The use of analytical engines enables the sharing of new insights. The evolution of

capabilities is shown in Figure 34.

Figure 34. Evolution of Progressive Levels of Analytics in Supply Chain Engines for Analytics

1. Descriptive. Visualization of data is the first step. With the use of descriptive analytics

companies can easily gain insights of data relationships without the deployment of engines.

2. Predictive. The use of predictive analytics enables the use of different forms of algorithms

to drive new insights. This includes linear optimization, genetic algorithms and stochastic

optimization. In each case there is a well-defined set of inputs, engines and outputs. These

run as batch processes within the supply chain. Predictive analytics are most commonly

used on historic data.

3. Prescriptive. Prescriptive analytics not only gives an output, but will also give

recommendations to exceptions. The most commonly used forms of prescriptive analytics

are in transportation routing based on road construction, traffic delays, and weather.

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4. Cognitive Learning. The use of machine learning to learn from data. Cognitive computing

starts with a rules-based ontology that structures the learning and then drives insights, over

time, based on hypothesis engines.

While predictive analytics is limited to structured data, prescriptive and cognitive analytics are

evolving to be used on nonrelational databases based on structured and unstructured data.

D) Delivery Mechanisms. Parallel processing and cloud-based delivery increases the options for

the buyer of analytics. While the traditional approach was licensed software with a maintenance

agreement of 18-22%, cloud-based deployments increase the options and reduce the costs.

1. License. Purchase of applications and implementation of the analytics through a license

deployment model including maintenance and implementation fees.

2. Hosted. Licensed software is run and managed by a third party and deployed via cloud-

based architectures. In the selection of hosted software, clearly understand the instance

architectural definitions and the limitations due to server sharing.

3. Software-as-a-Service. Solutions deployed natively over the internet. These cloud-based

architectures redefine maintenance and software upgrades. These applications are usually

purchased based on a number of users to use the software over a predetermined period of

time.

4. Business Process Outsourcing. In Business Process Outsourcing (BPO) services, a third

party drives the business process on behalf of their client. They use analytics through cloud-

based deployments to design, manage and maintain analytics software. The use of a third

party to provide not only software, but also the management and support team to run the

software to drive the analytics. Cloud-based services also enable the use of BPO as an

option.

F) Organizational Design. Determine how the solution will be used and who will maintain the data

models and inputs.

1. IT-Based Deployments. In traditional deployments, the software is maintained and

upgraded by informational technology teams. By definition, the use of relational databases

and reporting based on Enterprise Resource Planning (ERP) are IT intensive.

2. Self-service. To maximize the value of new analytics solutions, focus on self-service

deployments. These designs allow business leaders to drive their own reports and queries.

While the traditional analytics deployments were very dependent on DBAs (Database

Administrators), newer forms of analytics allow business users to own their applications.

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The Role of Analytics in Developing Strategies for Supply Chain 2030

As companies plan for Supply Chain 2030, and build strategic plans, analytics plays a major part in

the development of new capabilities. The relative focus of disruptive analytics is shown in Figure 35.

Figure 35. Role of Analytics in the Development of Supply Chain 2030 Strategies

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This evolution of Supply Chain 2030 strategies will be built on multiple, not one, analytics techniques.

The portfolio of analytics defining Supply Chain 2030 is shown in Figure 36.

Figure 36. Most Important Analytics Techniques in the Evolution of Progressive Levels of Analytics for

Supply Chain 2030

Today there are more options. The traditional world of analytics—with well-established terms and

technologies—is redefined. The first step is formulating the business questions. Build with the goal in

mind.

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Recommendations As you read through this report, we hope it stimulates thought and drives action. Here are nine

recommendations to consider in building your strategy:

1. Ask the Right Questions. Think Beyond Existing Paradigms. A frequent mistake companies make

is to focus only on technology. Start with the goal and work backwards. Train employees to ask the right

questions and use analytical approaches to drive root cause analysis. Use new forms of analytics to

unleash new insights.

2. Define the Metrics That Matter. Define a balanced scorecard and use analytics to drive frequent

updates of cross-functional metrics. In selecting the metrics for a balanced scorecard work with the

financial teams to set realistic targets. (Use of the Supply Chain to Admire report analysis can help you

to understand what is feasible based on industry-specific outcomes.)

3. Get Good at Managing Data. Data volumes are increasing and cleanliness issues abound. Get good

at using new forms of analytics to clean and parse data. Use cognitive and prescriptive analytics to

redefine master data management.

4. Build Strong Horizontal Processes. Success in horizontal processes improves alignment and drives

agility. The greatest success happens when the company is good at supply chain planning, and can

manage the horizontal processes holistically from the customer’s customer to the supplier’s supplier.

Don’t get caught in silos.

5. Not All Data Needs to Fly First Class! Move data at the speed that the business requires. Costs

escalate as data speed increases. While many supply chain strategies state that the data needs to

move real-time, the use of streaming data architectures (which are expensive) should be only used for

sensor and real-time event data.

6. Rethink Old Problems and Apply New Solutions. New forms of analytics offer opportunities to solve

old problems. Think past the status quo and drive new levels of performance. Test new technologies

and don’t accept that the current state defines best practices.

7. Think Beyond Three- and Four-Letter Acronyms. While traditional data architectures center on

reporting on SCM and SCE architectures, think beyond APS, CRM, ERP, SRM, TMS, and WMS

requirements in defining your strategy. Connect traditional architectures to workforce automation and

systems of insights by thinking holistically about data requirements and analytics.

8. Drive Innovation. Use techniques within the launch phases of innovation that embrace the world of

gray. Aggressively pursue process innovation that can drive success in new product launch.

9. Customer-Centric Supply Chain Strategies. Build processes to stimulate customer-centric

strategies, outside-in, with a clear understanding of what the customer values.

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Summary Supply chain management is three decades old, but there is great room for improvement. Horizontal

process evolution, new forms of analytics, and customer-centric processes offer promise, but will only

be effective if we can throw off the shroud of traditional supply chain thinking.

Primary Research: Reports Used in Compiling This Research in Review Report Over the period of February 2012 through December 2016, Supply Chain Insights published nearly

100 reports. Unlike other industry analyst groups—who keep their research behind a paywall—we

share research openly to help all global supply chain leaders. All of the research is archived in our

community on Beet Fusion for social sharing, on SlideShare, and updated regularly on the Supply

Chain Insights website. To gain a deeper comprehension of the research on these specific topics

check out the full analysis by clicking on these links:

Driving a Customer-Centric Supply Chain

In Search of Supply Chain Excellence

Improving Supplier Reliability

Putting Together the Pieces: Supply Chain Analytics

Why Is Supply Chain Planning So Hard?

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About Supply Chain Insights LLC Founded in February 2012 by Lora Cecere, Supply Chain Insights LLC is beginning its fifth 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 September 2015, and the fifth book, The Shaman’s Journal

2016, published in September 2016.

With over 12 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 speaks at over 50 conferences a

year on the evolution of supply chain processes and technologies. Her research is designed for the

early adopter seeking first-mover advantage.

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Endnotes i Putting Together the Pieces: The S&OP Landscape in 2015, 08/21/2015, Supply Chain Insights, http://supplychaininsights.com/putting-together-the-pieces-the-sop-technology-landscape-in-2015/ ii Supply Chain Visibility in Business Networks, 03/11/2014, Supply Chain Insights, http://supplychaininsights.com/supply-chain-

visibility-in-business-networks/ iii Driving Supply Chain Excellence, 6/18/2015, Supply Chain Insights, http://supplychaininsights.com/driving-supply-chain-

excellence/ ivInventory Optimization in a Market Driven World, Supply Chain Insights, 03/27/2015, http://supplychaininsights.com/inventory-

optimization-in-a-market-driven-world/ vMaximizing the ROI in Supply Chain Planning, 6/24/2014, Supply Chain Insights,

http://supplychaininsights.com/maximizing_the_roi_in_supply_chain_planning/