Data AnalyticsActionable insights to optimize operations and implement an on-demand supply chain for competitive advantage

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on-demand supp l y cha i nPerspectives paper

The Power of Data Analytics

Data Analytics & Functional Expertise = Increased Competitiveness

A global crop nutrients provider recognized the need to improve its competitiveness.

Data analytics and logistics experts worked together to provide executives with

actionable insights to help assess the cost benefit of 48 potential origin-destination route

options. This helped executives select the optimal location for their new $50 million

North American distribution operation.

Consequently, the company was able to:

• Get products to market five days faster than its competitors

• Increase market share 7% year-over-year in four consecutive years

• Reduce the company’s rail fleet by 50%

• Achieve $48 million in freight rate and fleet savings

• Release over $500 million in inventory and working capital

Source: Maine Pointe client

Products to market 5 days faster than competitors

7% increase in market

share year-over-year in four consecutive years

$48M freight rate & fleet savings

>$500M inventory &

working capital

released

1 2 3 4

ContentsDemystifying the terminology 1

The untapped market opportunity 2

Industries set to realize the biggest benefit 3

The challenges faced by the C-Suite 4

Turning data into dollars across procurement, logistics and operations 4

A key enabler for driving and tracking measurable transformation and change 5

Moving up the Data Analytics Maturity Levels to drive actionable insight 6

Data analytics in action 8

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on-demand supp l y cha i n

Demystifying the Terminology

The Internet of Things (IoT): The interconnection via the Internet of computing

devices embedded in everyday objects, enabling them to send and receive data.

Industry 4.0: The current trend of automation and data exchange in manufacturing

technologies. It includes cyber-physical systems, the Internet of things and cloud

computing. Industry 4.0 creates what has been called a “smart factory”.

Big Data: Extremely large data sets that may be analyzed computationally to

reveal patterns, trends, and associations, especially relating to human behavior and

interactions.

Data Analytics: The qualitative and quantitative techniques and processes used to

enhance productivity and business gain.

Total Value OptimizationTM (TVO): When an organization is dynamically able to

anticipate and meet demand through the synchronization of its buy-make-move-fulfill

supply chain to deliver the greatest value to customers and investors at the lowest cost

to business.

1

IoT

The internet of things is predicted to have a $14.4 trillion impact on the global market by 2022

The global internet of things (IoT) market will be $14.4 trillion by 2022 according to Cisco Research.

To put this in context, this represents approximately two thirds of US GDP. While the majority of

this will be invested in improving customer experiences, other key areas include investment in

reducing company time-to-market ($3 trillion), improving supply chain and logistics ($2.7 trillion), cost

reduction strategies ($2.5 trillion) and increasing employee productivity ($2.5 trillion). This will all have

a significant impact on companies’ abilities to open up new market opportunities, drive revenue and

margin improvement and achieve competitive advantage. There can be little doubt that companies

who don’t respond to this emerging reality will very soon get left behind.

The term industry 4.0 has gained popular status in recent times but others such as industrial

internet of things (IIoT), smart factory, connected enterprise, digital manufacturing and many more

are all used interchangeably and will drive the data revolution. When combined, these factors will

have a significant cross-organizational impact. From a value creation standpoint, as business models

and services evolve, we will see new ways of gaining competitive advantage. In terms of customer

experience, there will be growing emphasis on the individualization of products, services and processes

facilitated by higher human productivity, new work structures and roles, a safer working environment

and better security systems.

Industry 4.0 has been referred to by some academics as, “the fourth industrial revolution,” with the

power to revolutionize the way we, and markets, operate. Ubiquitous connectivity, smart technologies,

machine learning, artificial intelligence, and prescriptive analytics are not as far away as many may think.

Combined with the onset of cloud-based storage, this has resulted in an explosion in the amount of

data being stored, analyzed, interpreted, and is changing very the landscape we operate in. All of which

adds up to the fact that our ability to cleanse, categorize, interpret, and visualize business issues from

growing quantities of data is now at the core of future corporate survival.

The untapped market opportunity

Data Analytics

“The global Internet

of Things (IoT) market will

be $14.4 trillion by 2022.”

“Ubiquitous connectivity,

smart technologies,

machine learning,

artificial intelligence, and

prescriptive analytics are

not as far away as many

may think and will drive the

data revolution.”

“Our ability to cleanse,

categorize, interpret, and

visualize business issues

from growing quantities of

data is now at the core of

future corporate survival.”

2

Industry 4.0 - The Fourth Industrial Revolution

$3.7 trillionfrom improved

customer experience

$3.0 trillionfrom reduced time to market

$2.7 trillionin supply chain

and logistic

$2.5 trillionin reduced costs

$2.5 trillionin increased employee

productivity

Industry 4.0 - The Fourth Industrial Revolution

$3.7 trillionfrom improved

customer experience

$3.0 trillionfrom reduced time to market

$2.7 trillionin supply chain

and logistic

$2.5 trillionin reduced costs

$2.5 trillionin increased employee

productivity

Industry 4.0: The fourth industrial revolutionSource: Cisco Research

The manufacturing IoT market size is estimated to grow from $4.11B in 2015 to $13.49B by 2022,

attaining a CAGR of 26.9% according to Cisco research.

With the potential to streamline and deliver greater time-to-market and cost savings to a broad

spectrum of enterprise tasks, opportunities for internet of things (IoT) adoption are proliferating.

Many industry-leading manufacturers, service providers, software and systems developers are

already hard at work making IoT investments pay off. For evidence of this, we need look no further

than Microsoft’s May 2017 announcement. This states that Microsoft will build artificial intelligence

into every product and service it offers as decades of research start to break through into reality. This

includes unveiling new tools intended to democratize artificial intelligence by enabling machine smarts

to be built into software from smartphone games to factory floors.

From an industry perspective, manufacturing (27%), retail trade (11%), information services (9%), and

finance and insurance (9%) are the four industries that comprise more than half the total value of the

projected $14.4 trillion market. Cisco predicts smart factories will contribute $1.95 trillion of the total

value at stake by 2022.

The shift to operational data analytics

Over the past five years, data analytics investment has been predominately focused on the front-end

of the business to enhance the customer experience. However, many leading analysts and surveys

indicate that, given the level of investment in the IoT, emphasis is shifting to the back-end.

A CapGemini survey of more than 600 executives from the US, Europe and China, suggests that

this shift is driven by simple economics. Unsurprisingly, the main focus for executives is on the size

of the opportunity. Taking manufacturing as an example, the survey found that, by utilizing data,

companies could realize benefits of up to $371 billion globally. $117 billion of this stems from data-

driven operational improvement. Firms that capture these opportunities will lead the pack, deploying

predictive forecasting aligned with an on-demand supply chain and operational environment that will

enable them to capture market share, lower costs, release cash and improve profitability.

Industries set to realize the biggest benefit

Data Analytics

“With the potential to

streamline and deliver

greater time-to-market and

cost savings to a broad

spectrum of enterprise

tasks, opportunities for

Internet of Things (IoT)

adoption are proliferating.”

“$117 billion of this

stems from data-driven

operational improvement.

Firms that capture these

opportunities will

lead the pack.”

3

SmartFactorieswill contribute

Manufacturing isthe largest sectorthat is expectedto be impacted**

27%

$1.95T**

$117Bnopportunitydata-drivenoperationalimprovement*

Source: *Capgemini, **Cisco, and Maine Pointe

Predictive ForecastingSupply Chain OptimizationOperations OptimizationPredictive MaintenanceInventory Optimization

Low Costs & More CashEnhanced Growth & MarginCompetitive Advantage

$116Bn*

The C–Suite face many challengesAs the big data explosion continues unabated, research indicates that many executives struggle to

extract value and drive differentiation through data analytics. At best, companies have captured just a

third of the potential value from data analytics and the IoT. There are a number of reasons for this, but

the biggest barriers are often organizational as companies struggle to embed data-driven insights into

their operations, people and processes. Another challenge is attracting and retaining the right talent –

not only data scientists but business translators who combine data savvy with industry and functional

supply chain and operational expertise.

• Data not available in a timely, accurate, and consistent manner

for generating reliable insights and facilitate decision making

• Lack of in-house data scientists and data-to-business

translators

• Multiple customer crosswalks and a lack of a single truth

• Lack of harmonization across business processes and systems

• Erosion of trust in data over time

• Lack of ownership and governance, resulting in confusion

around who owns what data and what data sources are available

• Lack of data standards, data policies, and procedures

prevented data from third parties and commercial systems from

being effectively integrated

This is fueling the need for data analytics capabilities that combine deep functional knowledge with the

data science expertise required to translate insights into actionable business outcomes.

Turning data into dollars across procurement, logistics and operations

As the big data tsunami continues, advanced data analytics and predictive modeling is rapidly becoming

an opportunity for corporate differentiation to help drive increased EBITDA and profitability. Most

organizations simply lack skilled resources and, consequently, struggle to leverage the real power of

data analytics. Frequently, important market supplier, product, pricing, distribution, sales, marketing and

customer data is incomplete or resides in functional silos. This is hindering executives’ ability to unlock

Data Analytics

“At best, companies have

captured just a third of the

potential value from data

analytics and the IoT.”

“Another challenge is

attracting and retaining the

right talent – not only data

scientists but business

translators who combine

data savvy with industry

and functional supply

chain and operational

expertise.”

4

No data/ bad data

Limitations in analytical capabilities

Operationalization of analytical

outputs

“Data is incomplete or

resides in functional silos.

This is hindering executives’

ability to unlock the power

of data and the untapped

potential that resides within

procurement, logistics and

operations functions.”

Lead

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Data Analytics

Total Value OptimizationTM

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the power of data and the untapped potential that resides within procurement, logistics and operations

functions. By leveraging the power of analytics, executives have the opportunity to raise the level of

maturity across these functions to anticipate and meet demand through synchronization of the buy-

make-move-fulfill supply chain and deliver the greatest value to customers and investors at the lowest

cost to business. At Maine Pointe, we call this Total Value OptimizationTM (TVO).

A key enabler for driving and tracking measurable transformation and change

Senior executives are universally interested in meaningful tools to help communicate where and how

opportunities can be realized in their business to achieve high performance and competitive advantage.

Total Value OptimizationTM is an easily communicated scale of how any firm is performing in the critical

buy-make-move-fulfill supply chain across the critical dimensions of procurement, logistics, and operations.

TVO helps to illustrate how companies that adapt quickly and optimize value while becoming

increasingly customer-demand driven with a synchronized, informed, and forward-looking supply chain,

will not only survive, but thrive. Conversely, companies that don’t adapt are likely to face a steady

decline in market share, profitability and market presence.

Data analytics is a key foundation in helping companies transform their supply chain and compete

on value. It provides the bedrock of actionable insights that help clients identify, track, measure and

report on demand patterns and operational improvements as they move up Total Value Optimization

Pyramid™ to improve EBITDA, cash and enable growth.

Cross-functional expertise, change management and data analytics capabilities are the critical

components needed to drive synergy savings and a differentiated, on-demand customer service.

Data Analytics

5

Total Value Optimization (TVO) PyramidTM

Source: Maine Pointe

“Data analytics is a key

foundation in helping

companies transform their

supply chain and

compete on value.”

Improve insights to enhance supplier negotiating position

A further example is a global multibillion-dollar chemicals company which also had poor insight into

the performance of its supply chain. This was hindering their ability to negotiate better terms with their

supply base. Analyzing over three million invoice records that resided in multiple systems, our data

experts gave the client visibility of over $4 billion in spend. This on-demand approach to analytics

now gives them insight into contract terms and dates to enhance their negotiation and spend position

going forward.

Moving up the data analytics maturity levels to drive actionable insight

As companies start their Total Value OptimizationTM journey up the TVO Pyramid, it is vital to also

move up the data analytics maturity levels, which are directly aligned with the five levels on the

Pyramid. As they move up the levels they move from being reactive and backward looking to being

forward looking and innovative, continually improving the supply chain to create a differentiated on-

demand customer experience.

Aggregating and visualizing data across multiple domains is critical

Aggregating and visualizing information from big data, the client’s supply chain, and customer

behavior to deliver actionable insights is a critical requirement for companies today.

According to IBM, over a third of CEOs do not trust the information they are given to make decisions.

We experienced this first hand when executives from a global paper manufacturing company called

us in. They were struggling to make business decisions due to the poor integrity and visibility of their

data, which resided across four disparate systems. To overcome the problem our data analysts, as

part of a broader transportation engagement, cleaned and reduced duplicate records by 60%. This

directly improved the client’s customer service and sales forecasting abilities. Fuzzy logic techniques

were deployed to sustain data integrity and integrate it with the company’s network optimization

system for efficient transportation and enhanced performance.

Data Analytics

“As companies start their

Total Value OptimizationTM

journey up the TVO

Pyramid, it is vital to also

move up the data analytics

maturity levels, which are

directly aligned with the five

levels on the Pyramid.”

6

Data Analytics & Big Data

SupplierExperience

CustomerExperience

SupplyChain

Demand FocusData & Supply Chain Optimization

The TVO Data Analytics Bridge

Source: Maine Pointe

As companies move up the maturity levels they will typically experience the following journey:

Level 1 – Operational reporting: Concise informationThis is the most basic level of simple operational reporting. Data often resides in silos with basic reports,

often being produced manually, usually on spreadsheets. This more manual and siloed approach often

results in poor data integrity and visibility. Data analysts thrive in this arena by collecting and cleansing

data from multiple disparate systems. This naturally helps set the stage for conveying business

problems. Insights are typically driven by processing the raw data into operational reporting.

Level 2 – Descriptive analytics: What’s happening?For companies operating at level 2, executives typically are furnished with simple insights based on

past information. However, by deploying advanced analytics on historical/raw data, analysts can

begin to analyze past events for insight into how to approach future business problems. Data analysts

at this stage typically normalize and blend complex datasets. These are then used to mine financial

data and develop relationships between customers and products. This modeling is often referred to

as descriptive analytics.

Level 3 - Diagnostic analytics: Why did it happen?At this level companies start to become a bit more sophisticated at examining the cause of past results.

Data analysts deploy capabilities that allow for collaborative decision making. Organizations have

embedded dynamic dashboards that contain interactive visualizations and improve pattern detection

and analysis. These insights are found in the stage commonly known as diagnostic analytics.

Data analytics functional attributes by level

The TVO Functional Attributes Model is a pragmatic tool for mapping out where companies are and

where they want to go to achieve high performance in data analytics.

Data Analytics

“At level 5, executives

have attained a market-

leading position and

insight into existing and

emerging opportunities.

Executives will be able to

make proactive decisions to

achieve desired

business outcomes.”

7

5Prescriptive

Analytics

Description

4PredictiveAnalytics

3Diagnostic

Analytics

2Descriptive

Analytics

1Operational

Reporting

Dem

and

fo

cus

Tact

ical

fo

cus

• Demand-driven supply chain• Business optimization• Simulation modeling• Analytics drive business decisions and planning• Business and functional differentiation based on analytics

• Mature business intelligence and data governance• Visualization tools support business decisions• Advanced statistical optimization modeling• Dynamic forecasting• Risk analysis and mitigation

• Increased enterprise business intelligence awareness• Structured datasets and trigger-based insights• Slice and dice dynamic reporting and analytics• Large data sets routinely summarized to give insights• Automated, real-time dashboards from multiple sources

• Limited data management and insights• Centralized stored datasets and databases• Continued manual data collection and entry into spreadsheets• Simple data analysis• Business and departmental scorecards & KPIs

• Basic reporting and data silos• Ad hoc solutions, usually spreadsheet based• One-off data extracts and spreadsheet driven• Restricted access• Limited transparency into root causes

The TVO data analytics Functional Attributes Model

Source: Maine Pointe

Level 4 - Predictive analytics: What will happen? When and why?Once level 3 has been achieved, companies have reached a level of maturity that enables them to

understand the future and provide foresight by identifying patterns in historical data. Data scientists

will typically help with modeling performance and anticipate events. They will also be able to identify

correlations and leading indicators that derive rich insights for business decisions. This is known as

predictive analytics.

Level 5 - Prescriptive analytics: What should we do?At level 5, executives have attained a market-leading position and insight into existing and emerging

opportunities. Executives will be able to make proactive decisions to achieve desired business outcomes.

This is achieved through optimization techniques, machine learning and advanced operational environment

that unlocks the full value of the supply chain to deliver a proactive, on-demand, differentiated client

experience. Companies will be able to rationalize, optimize and automate decisions in real-time. These

dashboard-driven insights will influence business outcomes which is part of prescriptive analytics.

TVO data analytics in actionWith many executives still getting to grips with data analytics and how it can drive value for their businesses,

the following real-world success stories will help shed light on how many companies are benefiting from the

judicious deployment of data analytics across their organization as they move up the TVO PyramidTM.

Gain competitive advantage, save $48 million and release $500 million in working capitalOur data analytics experts, working with our logistics team, provided executives with actionable insights to help

assess the cost benefit of 48 potential origin-destination route options for a global crop nutrients provider.

This helped executives select the optimal location for their new $50 million North American distribution

operation. Consequently, the company was able to get products to market five days faster than its

competitors. This competitive advantage resulted in a 7% increase in our client’s market share year-over-

year in four consecutive years.

In addition, the Maine Pointe team helped to reduce the company’s rail fleet by 50%. This saved $48

million in freight rate and fleet savings while releasing over $500 million in inventory and working capital

for the business.

A global crop nutrients provider

Increase productivity improvements by 20% through advanced master schedulingWorking with a major chemicals company to transform their operations, our data analytics team defined KPI

metrics, deployed an effective data collection tool and implemented a proactive master scheduling system

that led to a 20% increase in productivity improvements and a 10% reduction in manufacturing costs.

A major chemicals company

Optimize procurement spend through insight into $4 billion of contractsBy analyzing over three million invoice records, our data experts deployed an automated spend cube that

gave a client visibility of $4 billion in spend. This provides on-demand analytics of spend leakage, contract/

non-contract %, MRO categorization and dynamic filtering across business units

enabling executives to enhance their negotiation and spend position

going forward.

A major chemicals company

Data Analytics

“By analyzing over three

million invoice records, our

data experts deployed an

automated spend cube that

gave a client visibility of

$4 billion in spend.”

8

DataAnalytics

Enhance demand planning for logistics and operations delivers $45 million

Working for a $50 billion energy company we delivered better control, greater accuracy and increased

visibility of the client’s aviation, ground transportation and lodgings divisions. By shifting the business to run

dynamic demand forecasting with predictive analytics to deliver advanced operations planning, we helped

the client save $45 million on sustainable basis across all 3 divisions and reduce carbon emission equivalent

to 2,173 vehicles taken off the road.

Major integrated energy company

Reduce working capital by 25% through demand buy-planning tools & processes

Working for a multibillion-dollar omnichannel mail order and electronic retail company, our data analytics

team, in collaboration with our logistics, procurement and leader and organization improvement SMEs,

transformed the company’s supply chain in the face of new disruptive business models. Focusing on over

100,000 seasonal SKUs we implemented new data analytics processes and buy-planning tools that helped

aggregate and normalize data from multiple siloed systems to reduce cost, enhance control and optimize

inventory levels. This was done in conjunction with installing a customized inventory management operating

system with a heavy focus on seasonal/demand planning to mitigate excess inventory and obsolescence.

This resulted in helping reduce working capital by 25% while improving management visibility and control

of their operations.

A multibillion-dollar ominichannel mail order and electronic retail company

Deliver 50% workflow automation to enable agile response to customer demand

A manufacturer of high quality newsprint, directory paper and paperboard was struggling with the fact that

data resided in silos across the organization: customer usage and purchase data in sales and marketing

systems, transportation data in operations databases, pricing and leasing quotes elsewhere. The lack of

visible coordinated forecasting & ordering protocols was having an impact with sales, production planning.

Our data analytics team worked developed a solution to streamline the creation of a network optimization

model that interfaced with multiple ERP systems and map source information. They automated data

workflows across the mills, significantly simplified the modeling process that allowed analysts to quickly

understand throughput and balance network utilization. This gave executives the ability to quickly adjust to

customer demand in significantly less time by producing a daily processing and shipping forecast for the

mills that can be changed rapidly for “what-if” analysis and use the data for ongoing modeling purposes.

This resulted in multimillion-dollar savings and 50 percent workflow improvement.

A manufacturer of high quality newsprint, directory paper and paperboard

Inventory optimization model identified over $1.2M of inventory reduction opportunities

Our data analysts, in conjunction with our logistics and procurement SMEs, helped a cross-functional

team at a global seating manufacturer create an inventory management strategy. Data analytics developed

critical elements to support the inventory program, including a customized analytics suite that was

connected to the client’s existing system and provided access to timely, accurate inventory data. The tool

also provided decision-based support metrics, adding a new level of transparency, visibility and insight. The

solution, based on inventory management best practices, led to a fast and sustainable inventory reduction.

Global leader in seating manufacturing

Data Analytics

“Our actionable insights

will help them negotiate and

build a win-win partnership

that will to lead to significant

cost savings and improved

time-to-market.”

9

About Maine Pointe Maine Pointe is a global supply chain and operations consulting firm trusted by many chief executives and private equity firms to drive compelling economic returns for their companies. We achieve this by delivering accelerated, sustainable improvements in EBITDA, cash and growth across their procurement, logistics and operations. Our hands-on implementation experts work with executives and their teams to rapidly break through functional silos and transform the buy-make-move-fulfill supply chain to deliver the greatest value to customers and investors at the lowest cost to business. We call this Total Value Optimization (TVO)™.

Maine Pointe’s engagements are results-driven and deliver between 4:1-8:1 ROI. We are so confident in our work and our processes that we provide a unique 100% guarantee of engagement fees based on annualized savings. www.mainepointe.com

Calculate the value potential of your business. Complete our TVO Self Assessment Tool and receive and automated Value Opportunity Report™. http://www.mainepointe.com/services/tvo-self-assessment-tool-video

This provides an indicative quantification of the value improvement potential (EBITDA & cash) across your buy-make-move-fulfill supply chain.

If you would like to discuss any points raised in this paper or would like to learn more about how data analytics can help you turn your data into dollars, email info@mainepointe.com

Telephone: +1 617.273.8450 (US) Telephone: +41.52.630.25.55 (Europe)