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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
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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.”
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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.”
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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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ITD
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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.”
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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.”
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5Prescriptive
Analytics
Description
4PredictiveAnalytics
3Diagnostic
Analytics
2Descriptive
Analytics
1Operational
Reporting
Dem
and
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Tact
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fo
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• 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.”
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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 [email protected]
Telephone: +1 617.273.8450 (US) Telephone: +41.52.630.25.55 (Europe)