Are You Ready for Merchandise Planning

8/10/2019 Are You Ready for Merchandise Planning

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Are You Ready For Merchandise Planning

Merchandise planning and control systems can play a key role in increasing profitability, but

how do you cut through the hype to find out if they are right for you? John Hobson, Managing

Director of The Planning Factory looks at some of the key issues. This article was originally

published in 1996 and was used as a source for the Financial Times Retail & Consumer

publication "Merchandising & Buying Strategies" in 1999. It was last updated in July 2008.

Very little has changed!

Merchandise planning systems have enjoyed a very high profile in the retail industry for some

time now. If you are contemplating implementing a planning system the first thing that you

will have to do is to make a business case for the project. Systems vendors have invested a

great deal of time and money in persuading retailers, quite rightly, that effective planning

can have a pivotal effect on bottom line profitability. How can we illustrate this?

With a typical cost structure a retailer can add up to 50% to bottom line profit by reducing

stock-outs and mark-downs by a couple of percentage points. In the example shown below

that means that profits increase by over 3 million pounds for a 100 million pound turnover

retailer.

Current Improved

Sales 114,285,714 114,285,714

Lost Due to StockOuts 12.5% 14,285,714 10.0% 11,428,571

Gross Sales incVAT 100,000,000 102,857,143

VAT @ 17.5% 14,893,617 15,319,149

Gross Sales ex VAT 85,106,383 87,537,994VariableCosts Intake Margin % 55% 55%

Gross profit 48,145,897 48,145,897

Cost of Goods 38,297,872 39,392,097

Markdown Loss 17.5% 14,893,617 15% 13,130,699


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Actual Sales Value 70,212,766 74,407,295

Actual Gross Profit 31,914,894 35,015,198

Fixed Costs Store Costs 23.75% 20,212,766 23.09% 20,212,766

Central Costs 11.25% 9,574,468 10.94% 9,574,468

Profit 2,127,660 +145 % 5,227,964

This reduction in stock-outs and mark-downs can only be achieved consistently by improving

the way in which stock is planned and managed.

Are these results really possible or are they just a plausible piece of bait dangled by over

enthusiastic salesmen? If we look at Hoogenbosch, the Dutch shoe retailer who run a chain of

over 200 stores in Benelux and have implemented IBM's Makoro software (Now sold by I2 as I2

Merchandise Planner), their own estimate of improvements is as follows:

In the last two seasons, stock turns have risen from 2.1to 2.5

Overall stock reduction of 12 percent; reduced stock ofup to 40 percent in some product categories

Increased gross margin by 1 - 2 percen Decreased markdowns by 8 percent Up to 25 percent more available open-to-buy

(source: IBM Case Study)

Another area in which savings can be measured is in human resources. In Retail Week,

February 27th 2004, a survey showed that a typical salary for a merchandiser in the UK stands

at between 30,000 and 40,000 pounds per annum. Let us suppose that our company has 10

merchandisers and that investing in a planning system meant that they no longer spent

Monday morning entering and preparing data. The half day saving in labour costs alone would

exceed 25,000 pounds each year. Assuming that they used this time in making productive

commercial decisions, then the additional return on investment could be many times this

amount, and on a continuous basis. Add this to the dividend from improved planning and you

have a very compelling case for implementing a planning system


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These improvements obviously involve investment in three areas, computer software,

computer hardware and human resources, all coming together to optimise the return on

investment in stock.

So we can make a case or investing in merchandise planning, but how do you decide if you are

ready to make this investment, and if you are, how do you go about choosing a system? To

non-specialists, merchandise planning can seem like a black art, but like most business

processes it is really just common sense. In this paper I want to try to demystify the process

of merchandise planning to help you to discover what questions you should be asking.

How do you decide if you are ready?

The first question that you need to ask yourself is whether or not you have effective core

operational systems handling the myriad day to day transactions. If your transactional systems

are not well established and understood by the users then you risk wasting your time and

money in trying to introduce merchandise planning. Assuming that you feel that you have a

mature core system, then you need to take a long hard look at your management culture.

Can you describe your organisation as information driven? Do your key executives understand

how to use the information provided by the system, and are they pro-active in trying to get

more from it?

These are positive signs that suggest that the time is right to start looking at merchandise

planning.

If you do feel that your organisation is mature in its use of information then you need to

decide whether or not you wish to make the change process evolutionary or revolutionary. It

is easy to be seduced by the sizzle offered by currently available products, without taking

into account the large investments that will be required to change the way in which your

merchandisers operate. Many projects have implementation costs that far exceed the cost of

system licences.


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You may need to decide whether you need a quick win first. This is most easily achieved by

automating existing processes. Once the quick win has shown the value of the approach, then

further process changes may be assimilated more readily.

The first step that you need to take in addressing this issue is to ask yourself what you expect

the system to achieve.

What should a system achieve?

To put it simply the goal of a merchandise planning system should be to maximise sales and

achieved margins by reducing stock-outs and mark-downs.

In order to achieve this there are a set of clearly defined stages that will be followed by most

retailers using a seasonally based planning system. Non-seasonally based systems will have

similar requirements, but will need greater flexibility in terms of time periods, and will use

different methods of extrapolation.

This list is not intended to be prescriptive. It is quite possible that you will wish to add to or

to change the list, but it does represent a set of the core elements involved in the process.

You should normally expect a Merchandise Planning System to be capable of providing a large

subset of the following:

pre-season analysis normalisation of base data plan seeding strategic planning (3-5 year time horizon) channel planning category level plan range planning store grading assortment planning line level planning store layout design (numeric and visual) in-season control and re-forecasting.


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Some systems on the market are focussed on the numeric side of planning and some

concentrate on the visual, qualitative side. It would be unusual to find a single system that

encompassed the entire list shown above.

Each module will consist of a set of inputs, processes and outputs. The overall process is

linear, but it is important that it should also be able to be re-iterated and the new results

rolled downstream through the system.

Before we look at these in more detail, though, we should first look at the issues that relate

to the scope of the system. The question of scope is really one of detail. What levels of your

product and branch hierarchies do you need to use in the planning process?

How much detail do you need?

It is important to realise here that, in practice, it is unlikely that you can cover all the bases.

There is an inevitable trade-off to make between accuracy and efficiency.

This is an area where the 80/20 rule applies. Each extra level of detail may marginally

increase the accuracy, but will require a comparatively huge increase in resources required.

For example, let us assume that we are generating a seasonal value budget and that we are a

100 branch retailer with 100 categories. If we plan at an all branch total level we will have

100 category plans to review. If we take the plan to individual branch level we will have

10,000 category/ branch plans to review. A halfway house here would be to provide a

mechanism for clustering branches with similar performance profiles and then dealing with

these together.

To some extent, however, the scope will be defined by the planning process that you select.

If you wish to plan using space by branch, then you will obviously have to maintain and store

base data and plan at an individual branch level. If your strategy is served well by your

creating a seasonal budget at an all branch level by category, then there is little to be gained

by including gratuitous branch detail.


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You will also have to accept that there are certain factors that will always be outside your

control. These would include the economy, distortions in weather patterns and competitive

activity. The fact that these variables can have a strong influence on actual performance is a

powerful argument for coming to a realistic compromise relating to the level of detail atwhich you plan. After all, the one thing that we can be certain of is that your plans will have

variances to actual performance!

Regardless of the levels that you select you are going to be planning at a summary level. Even

plans at style/colour/size level are summaries of individual transactions. This means that you

will have to bring data into the system and store it at the same summary level to avoid having

to recalculate the values every time you bring them up onto a screen.

The main message here is that every time you increase the detail in your plan, you vastly

increase the amount of effort required to create the plan in the first place and then to keep

it up to date. This is a point we should bear in mind when we are looking in detail at the

elements of a planning system. The main elements of a planning system Preseason analysis

Analysis is often seen as a separate activity, but in reality it is the foundation on which

effective planning is based. Most systems will offer some form of category level analysis inthe form of views of actual data as it gets imported into the system. At a simple level, pre-

season analysis can consist of reviewing these actuals before the planning process begins.

However, in order to create effective strategies, you really need to get involved in micro

analysis. This is typically down at the SKU, Store, Week level and ideally should make use of

attributes for both products and stores to allow meaningful summaries of the data. For

example we might want to look at summaries within a category by supplier in concession

stores (shop in shops).

The output of the pre-season analysis phase should be a clear statement of objectives for the

category, based on a full understanding of the historic weaknesses and the future potential of

the category.


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Normalisation of base data

In order to be able to make a sensible estimate of future performance, it is most likely that

we shall use historic data as a reference point. We need to make sure, though, that we are on

a level playing field. Historic data will contain all sorts of abnormalities due to such things as

promotions, branch refits, bad delivery, bomb scares, and moveable feasts like Easter. If we

are to use this data as a basis for extrapolation we must first remove these abnormalities.

This process is called normalisation. In addition to the removal of abnormalities, we might

also decide to use more than one years data, t aking, for example, a smoothed average of the

last three years. The result is a set of normalised historic data that we shall refer to here as

the base plan.

It is also true to say that the most difficult part of implementing a planning system is getting

good, reliable, clean data out of central transactional systems. In some cases the

"normalisation" process may need to include estimating data, or using existing plan data,

where actuals are not unavailable.

Another area where normalisation is necessary is planning the impact of moveable feasts like

Easter. Do not underestimate the time that this apparently trivial exercise can take if it is to

be done well. Plan seeding

The process of normalisation is closely linked to plan seeding, Indeed they are sometimes

done at one and the same time. Seeding is the process of creating the initial version of the

plan based on historical data. Whilst the use of historical data in planning has obvious

limitations, the alternative is to start from a clean sheet. This is neither desirable nor

practical. The accepted best practice here is to create an initial plan based on historical

data, normalise it and then to edit it by exception.

Strategic Planning

In a properly implemented planning system the process will have been designed so that it is

allows tactical actions to be taken to support the companys strategic plans. A discussion of


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It is important that your system allows you to re-iterate the process easily, as it is unlikely

that your first-cut plan will meet with universal approval. You will then need the ability to

flex the plan by making amendments at any of its several levels.

The outputs from the strategic plan are typically budgets for sales, margin and stock value

and units for a series of seasons, perhaps extending to up to 5 years, broken down to the level

of department.

Channel Planning

One of the key areas in merchandise planning is trying to assess the impact of store openings,

closures and refits, and the impact of any new channels such as E-commerce (the Net New

Channel effect). There is a considerable amount of debate as to when we should bring

channels into the planning equation. In most cases the principal impact of the Net New

Channel effect is on sales. There is not often a great change in key variables like gross margin

% as a result of new or closed stores, although it might be argued that the differing fixed

costs of bricks against clicks mean that this is worthy of more attention now.

A simple approach therefore is to take account of the Net New Channel effect in sales

planning and then to drive the rest of the numbers out using key variables like margin % and

weeks cover as planning inputs. It is for this reason that it is of key importance that whatever

system you select is able to keep these key variables fixed whilst allowing the sales budget to

be flexed and to recalculate outputs like profit value.

As with all planning modules you will be looking for a trade off here between detail and

usability. A typical plan will be at store level by week by department. This gives us the ability

to model product mix changes as well as openings or closures, but without creating huge

plans that are unwieldy to operate and check.

Another variable that you should consider including in your store plan is space. As we shall

see later on this is a key variable in the store grading process. Be aware though that

maintaining and planning space data requires considerable effort.


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One factor that is often overlooked when designing planning systems is that decisions relating

to store openings and closures often get taken much nearer to the time of action than is the

case with purchasing decisions. If you are going to create your merchandise plan 9 months

out, you need to ask yourselves if you will have any meaningful information about new orclosed channels at the time of planning. If not, then dont design store planning to integrate

with this stage of the merchandise plan (although do bear in mind that some sort of store plan

is essential in order to grade stores for assortment planning).

Weekly category level plan

Once we have incorporated the Net New Channel effect into our sales plan (if appropriate) we

can start work on our Weekly Sales, Margin, Stock and Intake Plan (often known as a WSSI).The mechanisms involved here are broadly similar to those used in the Strategic Plan. We are

simply moving one section of the plan (a seasons worth) down to a lower level of time (week)

and product (category).

This first stage of this plan will give us category level forecasts by week for sales, taxes (e.g.

EU VAT) markdown and margins.

I have been asked by clients "Why do we plan markdown?" Well, it is almost inevitable that we

will have to take mark-down losses. It is important that we plan these so that we can create

real forecasts of profitability based on planned achieved margins rather than on intake

margins. Mark-down is not a constant, and so it is necessary that we create a phased plan

here. However, as we shall see in a moment there is more than one way of defining and

planning markdown.

We already have a weekly sale forecast so this module requires us to flex the weekly

indicators for VAT %, Intake Margin %, Markdown%, Promotions %, Shrinkage % to give us the

resulting Achieved Margin %. This is a margin before the introduction of fixed costs and

reflects the sphere of influence of the merchandisers and buyers. For reasons touched upon

earlier it is imperative that we plan these relative percentages rather than absolute numbers


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so that if we flex our budgets the changes can ripple through in away that reflects the reality

of the business.

While deciding how to plan your margin you need to think about what methodology you are

going to use. Those of you who thought that margin was just sales minus cost may get a

surprise at this point.

In the USA and much of the Southern Hemisphere, retailers often adhere strictly to the Retail

Method of Accounting. In planning terms this means two things. Firstly your sales margin is

calculated automatically based on your available stock margin and secondly your permanent

markdown is applied to sales margin, in total, in the week it is actioned. European retailers

on the other hand, tend to use a hybrid method where sales margin is planned independently

of stock margin, and where the markdown applied to sales margin is either free planned or is

an automatically phased version of the permanent stock markdown.

(There is not space in this article to do justice to the relative merits (or otherwise) of each

approach, but readers interested in finding out more should feel free to contact me. Suffice it

to say that this issue can give rise to Merchandise Plannings equivalent of a religious war.)

We now come on to what is perhaps the key mechanism in achieving our aim of maximising

sales and minimising mark-down - open to buy planning.

Using our phased sales forecast we can generate a stock intake plan that closely matches our

intake with the stock requirement. This will probably be done at a category* level , and could

involve a variety of methods, the most common of which is to generate a periodic stock

requirement based on weeks cover. The difference between the stock requirement and the

commitments that we have a lready made is our open to buy. A commonly asked questionhere is Should we use flat cover or forward cover?

*Note that some retailers now take this process down to a category / product seasonality

level (e.g. Trousers, Spring/ Summer)


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Flat cover sa ys that if this weeks forecast is 1000 and we want 12 weeks cover we need

12000 of stock. Forward cover says that we need to cover the projected sales for the next 12

weeks. With volatile, seasonal merchandise the difference can be highly significant.

Forward cover generally creates more accurate results, but there is a price to pay. If we are

calculating the intake requirement for week 20 of a 26 week season and we are using 12

weeks cover, then we need to have a forecast for weeks 21 to 33. This means that we either

use week 26 over and over again, enter the stock requirement manually, or we need a simple

mechanism to project the next season at the same level of detail.

The depth of cover required in each period will be a reflection of several factors including

lead times, safety stocks, service levels required, price/volume trade -offs and closing stock

requirements.

It is also important to realise that we are really generating an open to receive rather than an

open to buy. If we want to receive 1000 units in month ten and there is a six month lead time

then we need to buy it in month four. An open to receive can be made up of goods bought in

several different periods. Once the open to buy plan is complete we are in a position to

optimise our cash flow, and our merchandise performance by bringing the right quantity ofgoods into the business at the right time.

Most planning systems also give the ability to convert appropriate KPIs to Cost and Units. To

do this we need to use average opening stock and intake prices and margins By inputting

these prices and margins we can generate the conversions required without the need for any

further effort on the part of the user.

Some planning systems find this a logical point at which to halt the formal planning process. Itis certainly the case that from this point on the process becomes more detailed, more labour

intensive and the returns begin to diminish. That is not to say, however, that it is not worth

persevering.


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Planning is about securing a competitive advantage, and the higher quality the plan, the

better the buying that will result from it. Having said that, there will always be a trade off

between plan quality and plan quantity. What an effective system will do is to allow you to

move towards greater plan detail without sacrificing quality or greatly increasing effort.

Range Planning

Having generated a category level plan we need to translate it into something that can be

bought. We may know that we plan to take 100,000 in Ladies plain v-neck sweaters and

generate a 40% margin on the sales, but we have to decide how many styles and options we

should have to achieve this result, and within these how many should we buy to achieve the

margin mix.

Decisions here are often soft ones. In other words the v alidity of historical data is

questionable and extrapolation can be dangerous. This is especially true of volatile

merchandise. We all know that it would be dangerous to say that because beige full length

skirts sold well last autumn that they will do so again next time. Equally, the breadth of a

range has as much to do with customer perception and the constraints of existing space as it

has to do with measurable trends. The lower limit of range width is often described as an

aesthetic minimum.

What we can do is provide systems that support buyers to help them out of the trap of buying

flat. They need to be able to support the winners, and to recognise that some of the styles

are probably for window dressing only - they might need to be there, but you do not need to

buy a container full.

In this context historical patterns can often be valid. In any typical category the ranked sales

participation of styles expressed as a cumulative percentage of total generates a surprisingly

consistent curve. For example, it is normal to find that the best seller in a group of ten styles

takes about 30% of the sales of the group. The best five styles will take about 85%, and the

last five styles account for the remainder. When represented graphically we call this

phenomenon a Rank Curve.


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both within and across categories. Finally you should be able to consolidate assortments up

you product hierarchy. Be aware that even some state of the art systems cannot do all this.

The usual gap analysis will need to be performed and any variances should be explained. We

do not need necessarily to close the gap. Plans are created and revisited at different times.

Given that we set ourselves some benchmarks with the strategic plan it is always important to

monitor against these. However, it is also important to recognise that circumstances change.

A flexible plan is a good plan - we just need to be able to explain why we have changed the

numbers.

Store Grading

If we accept that it is not practical to create ranges bottom-up for each individual store then

we need a way of grouping stores into grades to turn this process into something more

workable. There is a tendency to overcomplicate store grading resulting from an

understandable desire to cover as many bases as possible in the assortment process. Most of

us start off by looking at between 6 and 12 grades, and then some feel that they should go on

to add attributes to cover location type, demographics, climate etc. The danger here is that

we may end up with almost as many store grades as we have stores, which rather misses the

point of the exercise.

Efficient store grading for assortment planning should ideally be based on planned space as

this is the key determinant of range width in a retail store. (Web stores are a special case and

should be treated differently). If you dont have space data then you will probably use sales

performance to grade with.

There are several different methods you can use to determine the points at which each grade

starts and stops. At the most basic you can use equal splits and the more complicated

amongst you might like to see the effects of standard deviation in the planned data.


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Note: TPF have a ready to use model that allows users to grade by sales or space or a

combination using either equal splits, standard deviation or geometric progression to

determine breakpoints

Assortment Planning by Line

The role of the assortment plan is to define how we will distribute the styles selected.

Planning systems start to show wide divergences here with some restricting the plan to purely

numeric outputs and some providing sophisticated 3D animations of how the product will look

on fixtures. The key here though is that the limiting factor in retail is space. Any merchandise

plan that fails to take into account the constraints imposed by the physical environment risks

falling at the last hurdle. Allocating 12 styles to a shop that only has space to display 6 issimple begging to increase the seasonal mark down, at the same time as frustrating your long

suffering retail staff.

At a simple level retailers will assign a style to a distribution grade which will dictate which

stores receive it. Typically this will result in a wedge shape being created with larger stores

receiving greater depth of more styles.

At a more sophisticated level we might look at varying the initial, modular, range by store,

substituting items where demographics or climate variances suggest an advantage from so

doing.

Sales, Stock, Margin and Price Planning by Line

The final part of most planning systems is to break the category level plans down to a line

level. So what is a line level? In most cases we would advocate that this should be style

/colour but not style/colour/ size. This is purely on the grounds of manageability. This type

of module replicates the stock cards kept by most buyers / merchandisers, but being fed from

a centralised system is almost always an area of great efficiency gains. It is also where most

in-season monitoring takes place.


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If there are consistent variances from plan then we need to create a re-forecast and flush this

through the system again to recast our open to buy plans. This process might be automatic or

manual depending on the sophistication of your system. The essential thing to bear in mind

here is that our initial forecasts may have been mad e well in advance of the start of selling.The closer we get to the actual selling season itself, the more accurate our forecasts should

become.

So there we have the typical components of a merchandise planning system. When assessing

the offerings of system vendors you will find that each system approaches the issues with

varying strength and weaknesses, by far the most common weakness being in reporting.

Behind all of the systems lurk a variety of technological issues that need to be addressed.

Let's now take a look at some of these.

Technology Questions

Getting data into the system

Whilst your transactional systems are no doubt quite capable of generating endless reports,

you will not want your response times to grind to a halt every time somebody starts planning.

In all likelihood you are therefore going to house your planning system on a separate box.

Depending on the system you select, this box may be anything from a 1,000 PC running

Windows NT to 100,000 worth of tin sitting in a cool room, running on Unix with Oracle, and

bringing along it's own requirement for a database administrator who will cost you more,

annually, than the total purchase price of an entry level planning system.

Either way you are therefore going to need a discrete summary database to hold the

information. The buzz word for this is a datamart.

Getting data into the planning system is easiest where you have an automated process for

generating the information summaries and importing them into the planning system.


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You need to be sure that you have the flexibility to change or add to the data brought into

the planning system without incurring a lot of extra cost.

There are two common methods of getting data into your datamart.

The first is a push method where you export data from your main system as a text file and

then import it into the datamart.

The second is a pull system where you read the information into the datamart using Open

Database Connectivity (ODBC). ODBC is a standard for allowing applications to scan external

databases and suck data out of them using Structured Query Language (SQL). It has the

advantage that it gives you a live link into your transactional databases to refresh thedatamart, but it can be difficult to maintain and implement consistently.

The Database format

The datamart itself can take different forms. It may use the same (normally relational)

database format as your host system, it may be an OLAP (On Line Analytical Processing)

database. If it is an OLAP database it may be multi-dimensional (MOLAP), relational OLAP

(ROLAP) or hybrid OLAP (Like Microsoft Analysis Services). Multi-dimensional OLAP datamarts

present significant benefits in accessing and manipulating the data very quickly in many

different ways (dicing and slicing) and in simple format creation. Relational OLAP (ROLAP)

databases provide greater scalability, but can be less flexible, and less easy to implement.

The most basic planning systems use standard relational databases to provide low cost but

less sophistication.

Operating the System

Another important technological issue relates to the hardware configuration. Here again we

see a continuum stretching from the simple standalone PC to powerful mini-computers.


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Systems currently on offer include integrated planning systems provided by vendors of central

stock management systems, and highly specialised third party stand-alone systems that need

to be linked in to your host system.

Third party systems often use client-server configurations that require a dedicated server

linked to Windows based PCs. Do not forget to include the cost of providing PCs to those users

who do not already have them, but balance this with possible unrelated productivity gains

that can result. If a third party system is not fully PC based then you need to ensure that it

will run on your existing hardware, or accept the overhead of running another big box.

Integrated systems are often less sophisticated, often being designed to offer the minimum

functionality that allows a positive response to an Invitation to Tender. At the higher end of

the market, however there are some very interesting moves towards tight integration of

transactional and planning systems. The two downsides here are that even where it works as

advertised, this promised integration is very complex and is generally limited to those systems

that cost more than the annual stock purchase budget of your department.

However, it can be beneficial to have a single source for your software when it comes to

maintenance and updates, and only one head to bang when you experience problems.

Purchasing decisions should balance the positives and negatives of the above whilst being

based on your real needs and capabilities.

Implementation Issues

When you are evaluating the different systems on offer, you need to take into account the

costs and problems involved in implementation. These problems can be split into three areas

- cultural, organisational and data-related.

Cultural Issues

The first problem area is that of changes in corporate culture that will be required if you are

going to bring in a planning system.


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Change is inevitable when you bring in a new system, and, if it is to be effective, the planning

system will need an organisational framework as well as a computer system.

The key question, then, is how much pain you feel that your organisation can soak up whilst

remaining effective. The management of change needs resourcing and can be a very

expensive process whether it is controlled internally or by consultants.

You can take a revolutionary approach and implement a highly sophisticated system in one

hit, but you must make sure that you are in a position to resource, control and monitor the

change process.

Alternatively you can adopt an evolutionary approach and introduce the system in stages,making sure that each module is functioning properly and understood before you bring in the

next one.

The method of implementation that you adopt needs to balance your need to gain quick

benefits with the reality of the change process.

Whilst the change process is normally good for an organisation that manages it well, the

chances of a successful implementation increase dramatically when the system is seen to be a

servant of the process rather than the master.

You do not want to be told to plan a certain way because this is how the system does it. The

systems tail must not be allowed to wag the corporate dog.

Organisational Issues

The second problem area is organisational, and relates to the personnel who will operate the

system.

First of all you need to take into account the level of computer literacy of the staff who will

use the system. Once you have done this you need to make an estimate of the cost of training


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Repeating these mistakes will result in a vicious circle where little improvement is possible.

We need to create a virtuous spiral where better merchandising creates a better basis for

forward planning.

In order to achieve this there is a considerable amount of work required to interpret the

initial base data in the light of inadequate stock provision, overstocking, bad ranging and the

like. This process is required each time planning is done, but the load is greatest the first

time.

All of the issues discussed above will need to be built into the cost/benefit equation.

Getting the Most Out of the Implementation

Make sure you use the data!

In order to get the most out of the implementation you need to create a strategy for acting

on the information, and also to look for spin-off benefits.

To react positively to the new information you need to set up a control framework of in-

season review meetings with clearly defined actions that result from them. An end of season

review before the planning process begins again will also be of great benefit.

Without these controls you will miss out on a large part of the possible pay-back. The control

structure itself is one very valuable spin-off of the system implementation.

As well as reacting to the new information, there are also possibilities for being pro-active.

Look for external benefits

Efficient Consumer Response (ECR) programmes could be the subject of a lengthy article in

itself, but in essence it involves a partnership between retailer and supplier. The currency

used in the exchange by the retailer is information and that used by the supplier is service.


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Your forecasts and in-season re-forecasts have tremendous value if you share them with

suppliers, as they are then in a much better position to meet changes in your requirements.

ECR often uses Electronic Data Interchange (EDI) to transmit data, but this is relatively

expensive and complex and not strictly necessary. You can achieve a lot of the benefits witha free e-mail account!

Look for value added

If we are concerned with maximising the return on investment in planning systems, and

indeed systems in general, one area that is frequently overlooked is the value that is added to

data in the process of preparing the summary information used in planning.

Many planning systems make use of a datamart of summary information in order to reduce the

processing load on central systems caused by repeated query scans on transactional

databases.

What is often ignored is that the information in the datamart can also be used in periodic

management reporting.

A retailer who sees data on stock, gross sales, mark-down, net sales, profitability and cover

as being relevant to the planning process can also gain significant advantage from monitoring

the values stored during as well as after the season.

Indeed the technology that allows the views required for the planning process is the same as

that used in many cases within a typical EIS (Executive Information System). The multi-

dimensional database that allows structured access to planning data can also be leveraged in

providing this and different types of information to users throughout the organisation. For

example, similar summary information could be generated from financial databases to allow

financial budgeting and reporting.

Join up your planning


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It is amazing that many retailers buy one expensive system to do merchandise planning and

then buy another one that does basically the same job to do financial budgets. If you think

laterally and substitute a chart of accounts for a list of products you can save a lot of money

as well as integrating your budgeting process and making a reality of joined up planning.Wouldnt it make sense, after all if the sales, margin and stock forecasts in the company

budget were the same as the forecasts in the merchandise plan? Wouldnt it be easier to

achieve this if the same system were used for both? Whilst it may be unusual to see this,

clients with whom we have implemented such joined up plans see this as one of the most

significant benefits from the implementations.

Should you be doing it?

Having read this far, you may still be asking yourself if you should be really be considering

implementing a merchandise planning system.

Only you can answer this question but it is beyond doubt that improved stock management is,

and will remain one of the critical success factors for retailers in the 21st Century. It makes

no difference whether you are a bricks and mortar or internet retailer, you key responsibility

is to deliver a return on your companys investment in stock. You may apply different

pressures to the various levers, but the desired goal is the same.

Sales growth forecasts continue to be pessimistic and channels to market become more

fragmented and complicated to manage. Increases in profitability will only be available from

reductions in fixed costs or better management of variable ones. Most retailers have already

shaved fixed costs to the bone leaving better margin management as the only viable

remaining lever on profitability.

When you do decide to implement a planning system you will get benefits from four things.

First, by merely getting yourselves prepared to do it you will be forced to take stock of some

of the uncomfortable realities of your current position.


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Second, implementing the system will require a learning process that will be invaluable, and

the change process, if managed properly, will inject new enthusiasm into those involved.

Third, there are the concrete improvements in achieved margin that the system will bring

when it is used.

Finally there are the benefits that are available from the new possibilities that the system

creates, such as Efficient Consumer Response programmes, creating joined up planning by

integrating Merchandise Plans and Financial Budgets and better provision of information.

How should you do it?

To make the most of these possibilities you need to observe some general guidelines.

First of all, do not be seduced by technology. It is easy to become excited about the ability of

a system to change data by dragging points on a graph. Features like this are nice to haves,

but you must look past them to establish that the functionality that you need lies underneath.

Equally, dont assume that because one part of a system has certain functionality, that all

other parts behave in the same way.

Second, do not bite off more than you can chew. Your implementation is more likely to be

successful if you break it down into digestible sections. You must try to resist the temptation

to go for all the benefits at once.

Third make sure that you allow resources to define your requirement before you commit

yourself to a supplier. Remember that it is your requirements that must drive the selection

process.

Fourth, plan the implementation process properly, and make sure that you have proper

internal sponsorship at a high level.

Finally, measure the achievement. You are going to invest a lot of money in the system, and,

as far as is possible you, should try to evaluate the return.


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Implications for Systems Vendors

So, what does all of the above mean to systems vendors? The fact that users should be looking

for the easiest implementation path, and the ability to grow into a system means that

vendors must provide flexible systems that allow progressive sophistication.

The fact that users need to define their own needs and see these reflected in the system that

they buy means that vendors should not be over-prescriptive. Instead they should be enablers

providing

Core functionality Flexibility Consistent Interface

Access to base data Integration Expert advice

whilst allowing the retailer to retain control of the mechanics of the systems functionality.

Conclusion

In writing this paper I started with the goal of demystifying the process of merchandise

planning. Merchandise Planning brings with it a whole raft of new technology and jargon, but

you should not allow yourselves to be put off by this.

Merchandise planning is a complex process. George Davies, when he was at Next, maintained

that Retail is detail! and effective merchandise planning is one way that we can pay

attention to this detail.

Let us not forget though that retailing is about common sense. John Beddows, ex Managing

Director of management consultants Kurt Salmon Associates, used to maintain thatmanufacturing is a complicated business run by simple people and that retail is a simple

business run by complicated people (I think that this was his revenge for the amount of times

he had to listen to the joke about consultants stealing clients watches to tell them the time).


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Date post:	02-Jun-2018
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Are You Ready for Merchandise Planning

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