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CONTENT CREATIONPEERLESS
COLLABORATIVE ANALYTICS IN SUPPLY CHAINS
MAKING THE CASE FOR
2 • LeanDNA: Collaborative Analytics in Supply Chains • leandna.com
THE MODERN-DAY SUPPLY CHAIN is an intricate
animal that relies on many moving parts and pieces
to align and create favorable outcomes. For most
organizations, that means getting the right goods to the
right person at the right time.
Inventory optimization—that delicate balance of
capital investment, service levels, stock-keeping units
(SKUs), and the forces of demand-and-supply—
contributes to a favorable outcome by helping
companies keep pace with customer
demands, manage their suppliers,
stay ahead of shortages, maintain
optimal inventory levels, and drive
continuous improvements.
These are all big tasks in today’s
omni-channel world, where
increasingly-demanding customers
require deliveries in an Amazon-like
fashion—both on the B2C and B2B
sides of the equation. Meeting and
exceeding customer expectations in
a consistent manner requires solid
knowledge of everything from setting
the optimal minimum/maximum reorder points; key
“trigger” points; the correct order quantities; and optimal
order intervals (i.e., 30 or 60 days).
Getting all of these pieces in place requires moving
beyond spreadsheets and manual processes. Using the
same tools that have been around for decades doesn’t
work anymore, never mind that the information is usually
static and out of date by the time it’s ready for use. And
to complicate the situation further, the cross-functional
teams required to optimize inventory
are unable to work together
effectively to implement the required
changes, lagging behind in who is
taking which action, and agreeing
on how to achieve goals.
“Over the last 25 years, I’ve seen
hundreds of different processes
used by manufacturers to maintain
and analyze their data, but most
are labor intensive and involve
complicated spreadsheet systems,”
says Richard Lebovitz, LeanDNA’s
CEO. “Using a collaborative
Optimizing Inventory while Improving On-time Delivery with Collaborative Analytics
Just how many ERP screens, spreadsheets and emails between colleagues does it take to make good supply chain decisions? For most companies, the answer is “a lot.” Here’s how collaborative analytics bring people and data together to turn that tide.
“Using a collaborative analytics platform,
companies bring their data and people together
to solve challenging inventory optimization
problems and can now make impactful decisions faster and more confidently.”
— Richard Lebovitz, LeanDNA’s CEO
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
• LeanDNA: It’s More Than Graphs and Charts • leandna.com 3
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
most impactful inventory
actions to take is
basically impossible,”
Lebovitz says. “Using
our decision support
tool, the same procurement team can connect to its
existing ERP and use the combined intelligence to
provide specific inventory recommendations through
prescriptive supply chain analytics.”
The same intelligence can then be used to
enable multi-site collaboration and, finally, track the
results to make sure the action steps were taken.
This, in turn, can have a significant impact on the
organization’s bottom line. The same approach
used to optimize inventory and enable lower
inventory levels can also be used to drive improved
on-time delivery performance—the Holy Grail for
all manufacturers and distributors operating in the
competitive business environment.
“Collaborative analytics allow the VP of supply
chain who is running 10 or 15 sites to point his
or her finger at the problem, drill right down to a
single part, and understand what actions are being
taken (or that need to be taken), in just a matter of
a few clicks,” Lebovitz explains. “At the same time,
day-to-day users rely on the platform to continually
optimize inventory levels, improve customer service,
and ensure on-time deliveries.”
In this report, we’ll explore the key inventory
optimization challenges facing companies in the
current environment, show how a collaborative
analytics platform can help firms overcome these
hurdles, and hear from one company that has
reduced its global inventory by millions within months
of implementing the LeanDNA solution.
analytics platform, companies bring their data and
people together to solve challenging inventory
optimization problems and can now make
impactful decisions faster and more confidently.”
As you’ll read in this report, the benefits of
inventory optimization enabled by collaborative
analytics don’t end there. In fact, it allows
companies to tackle some of their most pressing
challenges head-on, including:
• The need to reduce working capital
• Getting the right parts at the right time to
improve on-time delivery
• Lack of standard work and best practices for
tactical supply chain management
• Getting stuck in a rut with manual processes
• Inability to be efficient and lean
• Misunderstanding the root cause of
supply chain problems (and what specific
actions need to be taken to improve the outcome)
• The list goes on…
UP AND RUNNING IN ONE WEEK
Leveraging the core principles of Lean, LeanDNA’s
cloud-based predictive and prescriptive analytics
incorporate the physical aspects of Lean (e.g.,
perform root cause analysis, set daily goals, measure
the results) into software that can be up and running
in a week or less. “It drives actions and measures
results,” says Lebovitz. For example, the automotive
supplier that sees its inventory levels and related costs
rising, but that doesn’t understand why, can use the
platform to quickly identify the exact cause of the
problem and determine which specific action will have
the biggest impact on the outcome.
“Procurement teams may see hundreds of ERP
messages a day, but determining the top five or 10
“Collaborative analytics allow the VP of supply chain who is running 10 or 15 sites to point his or her finger at the problem, drill right down to a single part, and understand
what actions are being taken (or that need to be taken), in just a matter of a few clicks.”— Richard Lebovitz, LeanDNA’s CEO
4 • LeanDNA: Collaborative Analytics in Supply Chains • leandna.com
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
AS THE WORLD’S SUPPLY CHAINS become more
complex and intertwined, effectively leveraging
data, making that data actionable, and then getting it
into the hands of key decision-makers have all become
imperatives for a broad range of companies. Historically,
extracting those advanced analytics from the IT department
and delivering them to actual users was a cumbersome,
time-consuming, expensive process that required an ERP,
multiple spreadsheets, phone calls, emails, and myriad
other tools.
A type of algorithmic decision-making that helps
companies optimize inventory decisions while providing
specific actions that they need to take to improve their
bottom lines, predictive analytics (here’s what will happen)
and prescriptive (here’s what you can do about it with the
goal to changing the outcome) analytics are replacing
the antiquated ways of leveraging analytics. These two
advanced data strategies converge to create a cloud-based
solution that provides all the data and reports supply chain
professionals require to gain visibility into today’s most
complex operations.
The Road from Manual Processes to High-Speed EfficiencyBy replacing antiquated, time-consuming ways of extracting actionable data and working together to solve problems, collaborative analytics help companies empower teams to deliver results.
“As inventory and supply chain systems become more
complex, they actually require more advanced processes
to translate that data and insights to help reduce inventory,
improve performance, and increase efficiency,” says
LeanDNA CEO Richard Lebovitz. “Embedded in our
LeanDNA technology is a prescriptive analytics engine that
is based on 25 years of experience implementing supply
chain and manufacturing best practices.”
DRIVING SUSTAINABLE SUPPLY CHAIN EFFICIENCY
LeanDNA takes the analytics fundamentals and
incorporates collaboration concepts inside the software,
enabling teams to work together to solve inventory
problems, surpassing basic spreadsheets, business
intelligence engines, and ERP databases by incorporating:
• Inventory data maintained and analyzed using supply
chain analytics software with specific features for inventory
optimization.
• Predictive analytics and/or artificial intelligence (AI) to
prioritize the most valuable inventory opportunities
• A high level of cultural accountability for team members
• LeanDNA: It’s More Than Graphs and Charts • leandna.com 5
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
(and the company as a whole). LeanDNA
creates transparency of assigned actions
and results, from individual buyers up to
aggregated site-level views, which drives
accountability across an organization.
• Extract and store data from any ERP
system or other data sources. LeanDNA pulls
information from any ERP system, translating it
and storing it into a common structure based
on manufacturing best practices.
Global companies with many
different ERP systems can view
data across multiple sites with
terms that are consistent and
easy to understand.
• Multiple people, sites, and
disparate ERP systems to pull all
inventory data into one place.
In return, companies can
effectively optimize inventory and
achieve a significant, measurable
increase in annual inventory turns. Other key
benefits include:
• The ability to document, track, visualize,
and understand inventory opportunities
throughout your company.
• A solution designed specifically for
inventory management based on industry
best practices.
• A platform that ties together all of the
important facets of inventory management,
including shortage reduction, supplier
management, and lean principles into a
single tool.
• A focus on standard work and best
practices that gives team members
specific daily tasks to optimize time
spent and value delivered.
• A culture of connectivity across
teams, sites, and ERP systems.
• Automatic root cause analysis to
understand the reason behind the
inventory issue or shortage, and
what specific action to take.
Daniel Taylor, LeanDNA’s Director of
Solutions Engineering, says the “culture of
connectivity” enabled by a cloud-based
prescriptive analytics platform helps
break down age-old silos that exist in
the manufacturing environment. “A lot of
companies are still managing very complex
processes offline,” says Taylor, “and with
siloed information.”
An aerospace manufacturer that utilizes
10,000 different SKUs to make an aircraft
wing over a 2-month span, for instance,
faces challenges every time a supplier
changes a part number or revises how it
makes a certain product. “There are a lot
of manufacturing dynamics that flow down
to the supply chain
group,” says Taylor,
“and that require
some real, tactical
decision-making in
order to optimize
inventory levels.”
The problems
only exacerbate when companies open
new physical sites, add new employees,
and attract new customers. Unfortunately,
ERP data that’s extracted and presented
as Excel spreadsheets just doesn’t cut it
anymore. Instead, the smart companies are
investing in a platform or a “unifying source
of truth” that helps them make good supply
“Our platform ranks those actions and not only empowers buyers, but also rolls right into
the C-suite, where executives can clearly see the impact that their teams are having at each site, and how those sites are performing
(or not). That’s the executives’ dream in a business world where their job is to improve
in as many areas as possible.”— Daniel Taylor, Director of Solutions Engineering, LeanDNA
chain decisions (e.g., it’s time to change
this order policy, place a PO with a different
supplier, or cut a certain order size in half).
“Our platform ranks those actions and
not only empowers buyers, but also rolls
right into the C-suite, where executives can
clearly see the impact that their teams are
having at each site, and how those sites are
performing (or not),” says Taylor. “That’s the
executives’ dream in a business world
where their job is to improve in as
many areas as possible.”
A MAGNIFYING GLASS FOR ERP
Because LeanDNA is prebuilt to
plug-and-play into an existing ERP,
the solution can be used through-
out every level of an organization,
where everyone from the supply
chain manager to the procurement
professional to the general manag-
er at a specific site can fully leverage the
prescriptive analytics it generates. This
data can then be leveraged in a way that
vastly improves and optimizes inventory.
“Our platform is essentially a magnifying
glass for an ERP,” says Taylor, “that auto-
matically generates actions that will have
the most impact on a daily basis.”
LeanDNA is unique in that it drives
value in all levels of the
business. Buyers and
analysts leverage the tool
to make their daily work
easier, and managers use
it to monitor and improve
performance and identify improvement
opportunities. By comparison, many
platforms are driven by executive
decisions, but then struggle to get user
adoption. In other cases, users get
excited about technology, but then that
technology fails to have a measurable
impact on the business.
6 • LeanDNA: Collaborative Analytics in Supply Chains • leandna.com
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
Using LeanDNA to Shave Millions in Inventory Costs
AS A WORLD LEADER IN AEROSPACE EQUIPMENT and systems for commercial, regional, and
business aircraft, as well as helicopters and space applications, Zodiac Aerospace has a long
history of developing and manufacturing state-of-the-art solutions that improve comfort and facilities on
board aircraft and high-technology systems that increase aircraft performance and flight safety.
Zodiac Aerospace’s procurement department moves from a spreadsheet-based inventory optimization system to a cloud-based platform that helps it prioritize, make good decisions, and improve profitability.
CASE STUDY:
Focused on delivering water and waste systems
for commercial aircraft—including those made
by Boeing and Airbus—Zodiac Aerospace’s Los
Angeles operation ships products to a worldwide
customer base. Up until this year, the procurement
team relied on ad hoc Excel reports comprising
columns, numbers, and dates that buyers used to
make their inventory optimization decisions.
PRIORITIZING INVENTORY
According to Gil Lenhard, VP of procurement, all
of Zodiac Aerospace’s prioritization of inventory
was done on a manual basis. “Trying to figure out
what we should do first was a constant chal-
lenge,” says Lenhard, who learned about LeanD-
NA’s cloud-based prescriptive analytics platform
from his IT department. “Some other business
“With this intelligence at our fingertips, we can figure
out the root causes of problems, try to avoid them, and do an overall better job
of bringing in material to support customer orders.”
— Gil Lenhard, VP of procurement, Zodiac Aerospace
• LeanDNA: It’s More Than Graphs and Charts • leandna.com 7
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
units here were already using LeanD-
NA. I watched a demo and could
see pretty quickly how useful and
powerful the platform was.”
In place for several months,
the prescriptive analytics
platform provides a new level of
visibility over Zodiac Aerospace’s
procurement operations. Lenhard
says he especially likes the
solution’s built-in algorithms,
which allow his team to prioritize
their inventory optimization
activities in the most cost-
effective manner possible. “We
always know what we should
focus on,” he says, “and which
decisions will have the biggest
impact on overall inventory
dollars.”
Because it includes purpose-
built supply chain dashboards and
analytics for Zodiac Aerospace’s
inventory, LeanDNA also gives
Lenhard snapshots of inventory
progression over time—something
he wouldn’t be able to access
using a standard report. “We can
see how we’re trending, which
is really important,” he explains,
“and whether we’re going in the
right or wrong direction.”
LEADING THEM DOWN THE RIGHT PATH
LeanDNA also shows Zodiac
Aerospace’s procurement team
which orders need to be placed
and provides it with a snapshot
into why certain orders need ad-
dressing and/or why they’re past
due. “With this intelligence at our
fingertips,” Lenhard says, “we
can figure out the root causes
of problems, try to avoid them,
and do an overall better job of
bringing in material to support
customer orders.”
Using LeanDNA’s prescriptive
analytics and purpose-built
dashboards, for example, Lenhard
can click on different reports to
view the largest impact-drivers
for a specific performance metric.
This not only tells him where
his team should be focusing its
efforts, but it also allows him to
“cut the data in many different
ways,” and leverage reports that
are easily customized with drag-
and-drop capabilities. “It’s pretty
intuitive,” says Lenhard, whose
team members use the data to
determine which POs need to
be placed first, which ones are
furthest behind and in need of
attention, and which ones need to
be rescheduled.
“If something has changed
and we no longer need a
product,” says Lenhard, “we
can take action quickly and not
wind up sitting on a mountain
of inventory.” Knowing that
those “mountains of inventory”
can quickly add up to major
investments and headaches,
Lenhard says he’s thrilled that
his team now has a modern
inventory optimization tool in its
technology stable.
“In the purchasing world, the
way to avoid problems is to make
sure you place orders on time,”
says Lenhard. “And with inventory,
the key is to be able to quickly
determine which levers to pull that
will have the greatest impact.”
Within three months, the
company has used LeanDNA
to help drive significant
reductions in inventory totaling
several million dollars. Lenhard
acknowledges a good portion of
his of his team’s immediate and
long-term success for inventory
reduction is tied directly to
LeanDNA, and his team
continues to use the tool every
day to find prioritized inventory
reduction opportunities.
“Analytics help us be more
proactive than reactive, respond
faster, and avoid problems
down the road.”
Within three months, Zodiac Aerospace has used LeanDNA to help drive significant reductions
in inventory totaling several million dollars
“If something has changed and we no longer need a product, we can take action quickly and
not wind up sitting on a mountain of inventory.”— Gil Lenhard, VP of procurement, Zodiac Aerospace
8 • LeanDNA: Collaborative Analytics in Supply Chains • leandna.com
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
Inventory Optimization and On-Time Delivery with Collaborative Analytics
The convergence of data and people inside a cloud-based collaborative analytics platform, built expressly for complex manufacturers, delivers real value to a company’s bottom-line.
FOR THE VP OF SUPPLY CHAIN: Tasked with maintaining a healthy supply chain, the VP of supply chain must be able
to cross-pollinate best practices across the entire organizational ecosystem. He or she also has to recognize problems
and solve them promptly—a mission that isn’t easy to accomplish across an entire group of manufacturing sites.
“When issues occur, it’s extremely difficult for the VP of supply chain to get out to multiple different sites and put his
or her finger on the root cause of the problem,” says Richard Lebovitz, LeanDNA’s
CEO. Key challenges include a lack of consistency in metrics being used, how they
are calculated, and the identification of best practices and rate performance levels
across all sites.
“They see issues with delivery or excess inventory,” says Lebovitz, “but don’t
really know which steps will have the most impact right now.” Using a cloud-based
prescriptive analytics platform, the same professional is suddenly equipped with
relevant intelligence (e.g., the root cause of the problem, the supply/demand profile, etc.) that can be used to make good,
impactful inventory optimization decisions.
These decisions not only solve immediate problems, but they also help to improve the firm’s customer service and
bottom line profits. “The platform knows what all of the common issues are, and it visualizes and displays those issues in
a way that the VP of supply chain can use to take the right actions,” says Lebovitz. “All of that intelligence also gets rolled
up for executives across all of their sites in a way that truly drives clear accountability.”
MAKING THE CASE FOR
• LeanDNA: It’s More Than Graphs and Charts • leandna.com 9
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
FOR THE CFO: Focused on the dollars
and cents of running a streamlined supply
chain, CFOs constantly have their eye on the
cash conversion cycle—or just how quickly
their firms can convert cash on hand into
inventory and accounts payable (through
sales and accounts receivables) and then
back into cash.
The LeanDNA platform makes this
calculation easy by measuring days of
supply/inventory turns and providing
analytics on inventory quantities relative to
demand. A factory that usually maintains
$10 million in inventory, for example, and
then increases that level to $12 million to
accommodate a 100% growth in demand,
has actually improved its inventory turn and
reduced its days of supply. However, if the
same company reduces its inventory to $9
million and then watched its sales drop by
50%, it should send up a red flag.
These indicators are invaluable to the CFO,
who is laser-focused on how such activities
impact the firm’s working capital. “Using the
LeanDNA platform, the CFO can easily assess
these positions and optimize inventory levels
in a way that improves the cash conversation
cycle,” says Lebovitz. The platform also
provides accurate and timely spend analytics
that CFOs are often left to their own devices
to locate and leverage. “They get reports once
a month but can’t really drill down to a root
cause of any specific problem,” says Lebovitz.
“In today’s business world, that’s just not
frequently enough.”
FOR THE CEO: As the highest-ranking
executives in a company, CEOs of
manufacturing organizations face unique
challenges where the supply chain itself
plays a critical role in both meeting demand,
as well as minimizing cash usage. They must
rely on the performance data being provided
and review the top actions from across the
entire company (versus specific sites).
CEOs also need a holistic, end-to-end
view of the supply chain in terms of materials
and movement within the factory. “The CEO
can be faster to react and be aware of pretty
much anything that’s happening in his or her
businesses at any time,” says Daniel Taylor,
LeanDNA’s Director of Solutions Engineering.
“They can also be proactive about fixing
problems and dealing with issues and
reporting on inventory-related issues to their
boards of directors.”
In the past, the same CEO had to ask
someone to create a report for him or
her, wait for that report, and then turn
around and present it via a PowerPoint
presentation or other format. “By the time
those steps are taken, the data is probably
at least a week old,” says Taylor, who adds
that LeanDNA’s quick deployment time of
a week or less also provides a high level
of value for busy CEOs. “We’re fast to
implement; the solution is out-of-the-box
and drives huge levels of value across the
organization,” Taylor says, “thus allowing
CEOs to almost immediately begin driving
bottom-line results.”
10 • LeanDNA: Collaborative Analytics in Supply Chains • leandna.com
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
Managing the Ever-Expanding, Connected Supply Chain
• LeanDNA: It’s More Than Graphs and Charts • leandna.com 11
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
“It doesn’t make sense to keep working in the past. If you want to be at the forefront of your industry, it’s time to adopt the technology that you need to work through
today’s challenges and prepare for the future.”
THE MANUFACTURING AND DISTRIBUTION ENVIRONMENTS are becoming more complex
every day. Where 20 years ago it was enough for an aerospace manufacturer to build aircraft that flew
efficiently, the same factory is now being asked to accommodate different seat arrangements; a wide variety
of cabin interior options; and myriad different colors, media devices, and other fine details. “The number
of options has proliferated and added a lot of complexity to the supply chain,” says Richard Lebovitz,
LeanDNA’s CEO, “across nearly all manufacturing verticals.”
To accommodate these trends
and their customers’ changing
preferences, manufacturers
are working with larger supplier
bases and outsourcing more
of their activities to their
business partners.
This is creating an
ever-expanding
supply chain that’s
not always easy to
manage or orchestrate
with manual or
spreadsheet-based
systems. “Sub-assemblies
and piece parts are being
outsourced to companies and
factories all over the world,”
says Lebovitz. “Without the
tools to identify and understand
where the problems are—and
then synchronize with internal
customers and business
partners—companies are
— Daniel Taylor, Director of Solutions Engineering, LeanDNA
having a hard time managing
that complexity.”
That complexity isn’t going
to ease up anytime soon, and
in fact is expected to get even
more complicated in the future.
“The manufacturing environment
is speeding up as customers
expect shorter and shorter lead
times,” Daniel Taylor, a LeanDNA
Director of Solutions Engineering,
explains. “Compound this with
the expanding product mix
and supply chain complexity,
companies are finding it very
hard to adapt using just Excel
spreadsheets and manual
inventory optimization
processes.”
And while those manual
processes may have sufficed
20 to 30 years ago, today’s
advanced technologies allow
companies to leverage the cloud
and data analytics in a way that
helps them stand out from their
competitors. “It doesn’t make
sense to keep working in the
past,” says Taylor. “If you want
to be at the forefront of your
industry, it’s time to adopt the
technology that you need to
work through today’s challenges
and prepare for the future.”
12 • LeanDNA: Collaborative Analytics in Supply Chains • leandna.com
MAKING THE CASECOLLABORATIVE ANALYTICS IN SUPPLY CHAIN
To learn more about leanDNA,
[email protected] • leandna.com