What is B_Line?
B_Line (which connotes bottom-line profitability) is a user - friendly profit-
maximizing yield management system/software for the Fashion Goods Retail
Industry. It is designed to aid decision-makers in arriving at optimal
inventory and pricing strategies, especially in the context of fashion goods
and other items with a limited life cycle. B_Line is a powerful planning and
decision support aid to the retailer.
Who is B_Line Meant for?
B_Line is a price optimization and markdown management software for fashion
retailers. B_Line is meant for anyone who is involved in the process of
decision-making with respect to procurement and markdown management.
Typically they would be
Retail Buyers
Merchandising Managers
Store Managers
B_Line would also be useful to managers in charge of purchasing at the
corporate
level.
B_Line can be used for showroom as well as catalog operations.
B_Line can be equally useful to planners and strategy formulators for
simulating market scenarios and studying their implications at the macro and
micro levels.
What does B_Line do?
B_Line uses data on demand estimates, costs, selling price alternatives, store
policies etc. as input - most of this data would be available through your
existing systems. Based on this data, B_Line works out optimal procurement and
price management strategy that would maximize profitability.
It works out
the optimal pricing pattern for the season as a whole given a plan of material
procurement
the optimal season starting inventory and the corresponding optimal pricing
pattern for the season as a whole
the optimal season starting inventory given a fixed pricing pattern
the profitability obtained for a given season inventory procurement plan and a
given pricing pattern.
B_Line covers both the "Markdown Only" and "Unconstrained" pricing policies.
Under the "Markdown Only" policy, prices either stay unchanged or go down as
the season progresses. In other words the price in a given period must be
either lower or equal to but never more than the price in the previous period
of the season.
On the other hand, the "Unconstrained" pricing policy permits prices to go up
or down in any period compared to the previous period.
B_Line uses statistical expected values for all optimization computations.
However, it projects simulated results for the Worst, Likely and Best case
scenarios, assuming that the market demand actually turns out to be minimum,
likely or maximum estimated.
B_Line takes the time value of money into account. All Dollar values are
discounted to a common time reference point i.e. the Season Beginning to ensure
that the optimization process yields "true" profit maximization.
How does B_Line determine the profit maximizing strategy?
B_Line incorporates a powerful numerical engine, which uses the immense
computing power of the current generation computers to intelligently scan
through a large number of possible courses of action using a Stochastic Dynamic
Programming model to pick out the strategy that maximizes profitability.
If inputs to B_Line are sound, the strategies suggested by it are likely to be
more profitable than those suggested by pure intuition.
What is the research underlying B_Line?
Our pioneering research in the domain of dynamic fashion retailer order
quantity and price markdown optimization models and algorithms began at the
University of Florida with the inputs our principal researcher Dr. Mantrala
received from retail merchandise managers at J.C. Penney’s. This led to the
development of the mathematical model MARK that has now evolved to form the
analytical core underlying “B_Line”. This research has been reported at various
stages, most recently in the May 2001 special issue on “Marketing Engineering”
of Interfaces, the applications journal of the Institute for Operations
Research and Management Science (INFORMS). This research was greatly aided by
inputs from fashion merchandising executives and Buyers at a number of
department store and specialty retailers including Filene’s Department Stores
(Boston, MA) Body Shop/Vogue (Jacksonville, Florida), Beall’s Department Stores
(Bradenton, Florida) and G.H Bass footwear (Maine).
Selected buyers worked with the research team led by Dr. Mantrala during the
mathematical model development and refining phases and provided crucial
insights into the field requirements. Subsequently, the model was tested using
real life data from the field.
Frequently, B_Line came up with counter-intuitive, apparently surprising
strategies that yielded substantially superior results i.e. strategies
generating higher profitability at lower outlays compared to intuitive
strategies currently followed in stores. The Buyers on further reflection came
to appreciate why these strategies were superior to their own intuitive
period-by-period tactics and came to appreciate that there was no way for them
to manually achieve the same results.
See case studies>>>>
What are the major insights that emerged from this
research?
Timing of markdowns is often more important than their magnitudes.
Optimal “Buy Quantity” and “Markdown” decisions are closely interlinked and
need to be made jointly rather than separately. How
much you buy depends on how you plan to markdown! And
how you markdown depends on how much you have bought!
Markdown strategies need to be adaptive as the season progresses – learning
from the actual market experience.
Taken correctly, markdowns are “strategic tools” for boosting profitability
rather than merely corrections for “buying mistakes”.
What input does B_Line require?
The major inputs required by B_Line are:
Demand estimates for different periods at different price levels
Inventory procurement plan in terms of the quantity of material that becomes
available for sale at different periods in the season
Different types of real and notional costs involved such as
- cost of goods
- holding or carrying cost
- cost of financing
- promotional cost
- stock-out cost
Permissible price levels for each period
Salvage price obtainable at the end of the season
Other information such as
- sales returns further broken down into usable returns
and unusable returns
- rate of deterioration and discard
- inventory shrinkage
Does B_Line include an Adaptive Learning mechanism?
Yes. Once the season gets under way, B_Line accepts actual sales data from the
POS systems and auto revises demand estimates for the rest of the season using
the Bayesian Revision technique. The actual sales and material receipt data is
also used to revise the inventory on hand for further processing.
Using these revised inventory and demand estimates figures, B_Line recommends a
reoriented profit maximizing strategy for the rest of the season.
What outputs does B_Line provide?
B_Line provides the following output:
Optimal period wise pricing strategy given an inventory procurement pattern
Optimal season starting inventory and corresponding optimal pricing strategy
Optimal season starting inventory given a specific pricing strategy.
B_Line then goes on to project a wealth of decision support information both at
the period (detailed) level and season (summary) level.
- Sales revenues and profits
- Cost analysis
- Cash flow analysis
- Opportunity loss analysis
Information is presented both in physical as well as value terms. B_Line
provides an array of striking graphical presentations so that the user
registers all essential decision support information.
Does B_Line provide for Simulation of different
scenarios?
Yes, B_Line provides for simulation of the worst, likely and best case
scenarios so that the user is clear about where the B_Line suggested course of
action falls within this bandwidth of possibility.
Does B_Line integrate with other systems?
B_Line is designed to function in concert with your forecasting, POS and
Inventory systems.
B_Line can directly work with popular databases such as Oracle and MS SQL
Server.
Once integrated into your systems at implementation time, B_Line functions as a
part of your work environment along with your other systems to provide you
on-going decision support, effortlessly, profitably.
On what platforms does B_Line operate?
B_Line operates in the Windows environment.
What size retailers can benefit from B_Line?
B_Line can be implemented both in small as well as large retail organizations.
B_Line can be used as a desktop decision support aid by smaller fashion retail
establishments. In the larger organizations, B_Line can be integrated with
their Demand Forecasting, POS and Inventory Management systems for on-going
systematized support.
How does MMI help?
MMI is organized to assist in all aspects of the implementation process,
as required i.e.
- User training
- Software customization
- System integration
MMI also provides advisory services to retailers in other areas of their
operations that include retail pricing, category management, advertising
scheduling and marketing resource allocation decisions.
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