What You Need to Know
About the New Collaborative VMI
The
last few years have been challenging. The silver lining is that companies have been
forced to re-evaluate how they operate, inspect every process, and identify
what and how to improve. Recently, AMR Research indicated that the global
economic downturn and the need for improved inventory visibility and efficiency
has led to a recent resurgence in vendor managed inventory (VMI) programs.1 As a result, many companies
have turned to closer collaboration with key partners as a way to improve
efficiency, reduce costs and drive a more profitable supply chain.
VMI
today is quite simply not the same as it was just a few years ago. It is no
longer a one-sided process that burdens the seller and benefits only the buyer.
In its early days, VMI was widely hyped to dramatically reduce inventories, cut
costs and improve efficiency across the supply chain. It did accomplish its
goal to reduce supply chain costs; however, its key hurdle and reason for the
lack of continued support was the absence of true collaboration.
Today,
we see the traditional data intensive VMI process merging with the best of Collaborative
Planning, Forecasting and Replenishment (CPFR) to form Collaborative VMI, a new
process which shares more of the benefits across trading partners. This
whitepaper examines how traditional VMI and CPFR have come together to form a
more encompassing process. As the economy recovers and demand picks up,
collaboration is key to ensure that service levels remain high while inventory
levels remain lean.
A Look Back: VMI
& CPFR
Vendor
Managed Inventory is a means of optimizing supply chain performance in which
the seller is responsible for maintaining the buyer’s inventory levels. The
seller has access to key buyer information including inventory and point of
sale (POS) data. Here, the seller’s task is to ensure that the buyer’s
(customer’s) inventory levels do not go lower than what is agreed upon. Sounds
clear except the conversations tend to be one-sided, push-based interactions.
For example, “How much inventory does my buyer have? What is the threshold
before I need to manufacture/ship new stock?”
According
to an AMR Research (now Gartner) survey, companies that employed a traditional
VMI relationship felt a “nagging sense of unfulfilled expectations.” The
fanfare, as the report calls it, did not meet with the reality of VMI.2 However,
the report goes on to say top-performing organizations “have used their
VMI-driven collaborative relationships to increase presence in their partner’s
(retail) operations.” Others have seen a reduction in customer returns due to
improved operational execution and the ability to collectively build a
“stronger analytical understanding of customer behavior.”
Alternatively,
CPFR allows trading partners to collaboratively review sales and order
forecasts, and share data to the benefit of both the buyer and seller. The CPFR
model outlines the basic framework for the flow of information, goods and
services between two trading partners (buyer/ seller). Under this process, trading
partners develop a joint business plan to identify the terms of their
relationship including areas of responsibility, jointly developed calendars,
guaranteed customer service levels, timing of replenishment orders, etc. In
many CPFR arrangements these plans are defined in a formal agreement. The key
addition to CPFR is the ability to allow for exceptions to be a part of the
process, which delivered improved visibility and process scalability.
While
VMI has been thought of as a static, legacy process, the CPFR model was
perceived as a highly structured and time-intensive process that some trading
partners were unable to adopt. Some companies started CPFR initiatives but
failed to achieve a comprehensive rollout. In an October 2010 Gartner report, a
manufacturer stated that “CPFR was originally intended to achieve this
objective [real-time demand sensing], but it fell short for a confluence of
factors, including lack of trust, siloed organizations and inflexible planning
systems.”3
Tangible
results from VMI and CPFR have been documented. The issue is the number of
roadblocks the legacy processes created. According to Logility’s polling,
results from VMI and CPFR are significant (see Table 1).
An Evolution to
Collaborative VMI
With
documented benefits of both VMI and CPFR, and the growing need for increased
inventory visibility, improved forecast accuracy and better customer service, a
more strategic form of VMI evolved. Enter Collaborative VMI. The goals for
Collaborative VMI are to 1) develop a process that partners want to get on
board with, and 2) provide a tangible benefit to both parties without the
distraction of too many steps.
The
premise behind Collaborative VMI is to make sure all trading partners
proactively talk and work with each other to share information. Suppliers
should not blindly react to a retailer’s inventory level and a retailer must
not be caught off-guard due to a slippage in lead times resulting in empty
shelves. Nor should partners need to worry about a laborious process to ensure
information is shared in a timely fashion. Instead, a Collaborative VMI process
should entail:
·
Engage
in proactive meetings to discuss the process and on-going relationship
·
Shared
visibility of promotion plans
·
Visibility
of New Product Introductions (NPIs) to the supply chains of both trading
partners
·
Partners
should jointly develop and validate the baseline forecasts
·
Create
an environment of trust where each partner shares pertinent information
including manufacturing plans and downstream data to alert trading partners of
any potential problems
Get the Basics Right
As
with any process where sharing information with external partners is key to
success, having strong internal planning processes in place is paramount. Two
of the critical supply chain processes that need to function properly before
starting down the Collaborative VMI journey are 1) Demand Planning and, 2)
Inventory Optimization.
Demand Planning
An
accurate customer-level forecast is the foundation for achieving your
Collaborative VMI goals. But how do you create an accurate forecast? And at
what level of detail do you generate and manage the forecast? Does the same
apply to New Product Introductions? Have you synchronized the promotional plans
of your trading partners?
Here
are some critical points you should consider to ensure your demand planning can
support a successful Collaborative VMI partnership.
1)
The ability to automatically generate an accurate forecast. Forecasting
algorithms that automatically detect product seasonality or irregular demand
patterns will get the forecasting process off to a great start
2)
Scalability is a critical capability as you typically need to generate
forecasts at the customer/ ship-to level of detail for your VMI partnerships
3)
Managing New Product Introductions introduces a number of unique challenges
that most statistical forecasting solutions cannot solve. Solutions that offer
attribute-based forecasting models will greatly improve your ability to predict
future demand for products that have little to no demand history
4)
A key improvement of Collaborative VMI is the ability to model your trading
partner’s planned promotional activity. Sellers need the ability to model
changes their customer’s changes to the baseline forecast. The ability to model
multiple promotional activities such as price changes, advertisements, or
special packaging will assist sellers in understanding the lift, or anticipated
increase sales volume
5)
Having visibility into the impact of additional sales due to trade promotions
allows the supply chain team to automatically model multiple replenishment and
supply strategies
·
Pre-build
product – If you are in a constrained manufacturing environment, do you start
pre-building product in anticipation of demand? How early do you start to build
product?
·
Alternate
Sources – Can you source the product from another manufacturing site?
·
Make
vs. Buy – Typically you may manufacture this product but with the increase in
demand you may look to outside co-packers to provide additional capacity and/or
assist with production
Inventory Optimization
The
ability to optimize inventory across multiple echelons, with global visibility
of customer service commitments, costs, and demand and supply variability, is
an inherent need in every complex supply chain and for every successful VMI
project. The setting of inventory targets and how to fulfill those targets is a
top objective of a VMI relationship.
There
are many competitive benefits to right-sizing inventory in a collaborative VMI
relationship. Here are five examples of how multi-echelon inventory
optimization (MEIO) can positively impact the VMI partnership:
1.
Inventory reduction – cut the amount of excess inventory, such as safety stock
held throughout all stages of the supply chain, without harming service levels
2.
Reduce working capital – reduce excess inventory to release a proportional
amount of working capital that has been trapped in unnecessary inventory
investment
3.
Logistics cost savings – reduced inventory saves associated costs, such as
labor, warehousing, expediting, and more
4.
Lower obsolescence cost – improved obsolescence rates reduce write-offs of
obsolete finished goods inventory
5.
Revenue uplift – better inventory alignment translates into the ability to
satisfy more sales orders which increases top-line sales revenue.
5 Steps to Ensure
Collaborative VMI Success
So,
you are ready to dive into Collaborative VMI. Before you do, make sure you
follow these five steps to ensure your success.
1.
Select the Right Trading Partner
While
it may seem obvious it is absolutely the most important step to get right. You
need to select the partner(s) that shares similar business values. You will be
sharing sensitive information with someone outside your organization and the
ability to trust them is paramount. As part of this, take the time to
understanding your strengths and weaknesses as a supply chain organization as
this will help determine the optimal collaborative framework. Evaluate yourself
as well as potential partners, do not rush through this step.
2.
Be Flexible
As
with any defined process it is important you remain flexible. Goals and
objectives may vary with each trading partner. In some cases inventory fill
rate may be the top objective, in others inventory turn rates and yet in others
forecast accuracy. Remember, the Achilles heel of the original CPFR was its
rigidity. You need to maintain flexibility throughout to keep the balance and
drive mutual benefit with your partners. Once you have a proven process
successfully established, use it as the template for working with other trading
partners.
3.
Document the Expectations
It
is critical to document in detail the goals and objectives for the VMI program.
For the customer it may be increased fill rates and better visibility of
supply-side information. For the seller, the focus may be on inventory turns or
visibility into promotional plans.
It
is critical to document a clear and concise definition of goals and how these
goals will be measured. This way each party understands and works towards the
same goals in true collaborative form.
4.
Understand the Data
Defining
the data requirements and the sources of the data are the key technical tasks
in the deployment of Collaborative VMI. Key required data includes:
·
Point
of Sale
·
New
Product Introductions
·
Inventory
transactions
·
Baseline
forecasts
·
Planned
promotional activity
·
Planned
replenishment orders to the buyer
As
you can imagine there are many challenges when integrating data from two or
more disparate systems. What item number do we use? The buyers? The sellers?
Does our VMI system support item cross reference so that each party can use
their own item number? Are both trading partners planning in the same time
periods? Are the time periods aligned? For example, both parties may plan in
weekly time intervals, but does the week start and end at the same time?
This
can quickly turn into a complicated matter without the right supply chain
planning tools. For example, inventory optimization (IO) is a key function that
many companies strive for and in a Collaborative VMI relationship,
understanding the optimal locations for inventory in a multi-echelon
environment and IO’s impact on partners can dramatically change the
effectiveness of a program.
5.
Automate Where Possible
Collaborative
VMI is based on the blending of the traditional VMI process with the more
collaborative approach of CPFR.
There
were two key issues with the original VMI process. First, it was a data driven
process that did not easily allow for manual intervention. Data was transformed
and transmitted via EDI from one trading partner to another. Systems made decisions
based on that data and rightly, or not, replenishment orders were generated.
The second issue was a lack of exception management. There were few, if any,
process alerts built into the original framework. While alerts were present on
the seller side, such as “the seller is planning item ‘A’ but the buyer doesn’t
have item ‘A’ in their plans,” there was no alert in their planning process
that told them “the seller’s forecast for item ‘A’ changed by ‘n’ percent since
the planning cycle.” These anomalies could greatly impact both parties’ ability
to satisfy demand.
The
main concern with CPFR was that it was seen as too rigid and time consuming
because many companies managed it in spreadsheets. While this was partially
corrected in future releases, the perception still remains to this day.
Collaborative VMI, however, takes a better approach—automating where possible
and alerting key parties when needed.
Case Study: VMI in
Food Manufacturing
A
manufacturer which supplies one of the world’s largest food manufacturers with
plastic containers historically worked off of the buyer’s min/max thresholds to
determine how much product to produce and ship. This approach required a
balancing act on the seller’s part to ensure they always held the right amount
of inventory without over / under producing.
In
2009, the trading partners moved towards a collaborative vendor managed
inventory relationship. The seller now receives 18 months of information every
day including on-hand inventory, daily production requirements and safety
stock. This information is provided to its demand planning system, to drive a
comprehensive time-phased supply plan. With this increased visibility, the
seller is able to replenish inventory based on daily stocking levels and ship
at its discretion.
The
information received by the system allows the seller to generate a
customer-level forecast and then compare that with its customer’s. It also
provides the seller with a customer-level plan that can be analyzed in the
context of its broader business. The ability to collaborate back and forth and
analyze each forecast has allowed the seller to gain better control of its own
inventory, and keep it at minimal levels while ensuring top customer service.
The customer is now able to share promotion information and provide the lead
time the seller needs to ensure the availability of new artwork for packaging
as well as increased volumes during peak selling times.
The
two partners have established regular, proactive strategy discussion to
collaborate on how to improve the process and help each company ultimately
achieve its goal of more efficient operations that reduce costs and improve
service levels. This collaborative approach has led to:
·
Inventory
reduction of 15%
·
Sales
increase of 6%
·
Annual
inventory turns improvement of nearly 25%
·
Removal
of 7 full days of inventory from the network
·
Improvement
in on-time service delivery from 94 to 98.5 percent, with less inventory
Case Study: Getting
Dressed with VMI
One
of the world’s most recognizable apparel brands had the perfect storm of high
inventory and low fill rates. Its’ use of spreadsheets was not a long-term
strategic plan and focused the supply chain team on tactical activities. The
company realized the focus on short-term planning would not enable them to
achieve goals of shorter lead times, improved inventory management, reduced
working capital requirements, or improved fill rates. In addition, this
tactical approach made it very difficult to increase collaboration with
customers, obtain better visibility into demand patterns and develop long-term
supply chain plans.
To
reach its goals, the company implemented a new software solution and after
improving their in-house supply chain systems, they decided the next step in
improving customer service levels combined with lower inventory levels was to
deploy a VMI strategy with key retailers.
The
apparel company’s sales team was able to use VMI as an additional lever to
increase shelf space and improve placement of their products at retail. Why?
With better planning the supply chain team felt confident they could deliver on
the promised metrics such as guaranteed service levels, improved perfect order
delivery, correct mix of product, etc. After deploying to a select group of
retailers, the apparel company quickly grew into deploying VMI relationships
with more than 25 of its key partners. Moving forward, the apparel company
wants to deploy VMI relationships with their key finished goods and fabric
suppliers in a continuing effort to improve supply chain efficiency.
With this aggressive approach to supply chain excellence, their CEO stated in the company’s annual report that “We manage our balance sheet conservatively, maintaining the right inventory levels, and we are doing $1 billion more in sales on the same level of inventory we had four years ago.”
Other
benefits realized include:
·
More
effective and objective decision making as a result of quicker access to
fact-based data
·
Higher
confidence in data integrity and accuracy significantly reduced time required
for reconciliation
·
Stronger
trust based partnerships to support true collaboration
·
Greater
visibility to current and future issues, constraints, and opportunities
·
Reduced
weeks of supply 67%
·
Increased
customer fill rates from 97 to 100%
·
Reduced
forecast error rate by 50%
·
Decreased
manufacturing lead times by more than half, accelerating its cash-to-cash cycle
Contributed by: Jonathan Jackman, EMEA Sales Director, Logility Supply Chain Solutions
