I graduated from Imperial College, London with a degree in Mining Geology, and then joined Andersen Consulting (now Accenture). After 6 years there, I moved to Berkeley. I have had the privilege of wo...
Juliet Armstrong, Partner
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Finding the best route - driving out costs at M&S
Home > unspun 22 > Finding the best route > Finding the best route - driving out costs at M&S
M&S operates 50 outlet stores across the UK, which provide a channel through which to move excess stock from the main chain business at reduced prices. Excess product can arise for many reasons; consumer reaction to the product launch is not as strong as expected; a wet summer depresses typical demand for sundresses; an entrepreneurial supplier offers an attractive deal to make a run of t-shirts from some excess rolls of fabric left over in the factory; or main chain stores want to cycle stock post a big sales event. The complexity of the Outlets business lies in that the selling season for a particular product – cashmere jumpers for example – is often limited and has to come back around before the product can be offered anew to Outlets customers. This can require stock to be held for up to twelve months before it is again “season relevant”. Due to its “last season” nature, the customer expects Outlets product to be attractively priced, requiring a highly efficient operation as the already tight margins have been halved.
Following a period of strong growth from inception through to 2008, more recently the growth rate has slowed as the Outlets market has matured. Nevertheless, M&S still consider there to be a sales growth opportunity, albeit
one that entails further price discounting and hence increased product volumes.
Logistics costs obviously increase as volumes increase, however the forecast 19% increase from 2009/10 to 2010/11 was double that of the expected sales growth in the same period. Richard wanted to fully understand the drivers behind the cost increases, and how the main chain logistics strategy may impact on costs to Outlets in future. He then wanted help developing a strategy to address these challenges, by identifying and quantifying cost savings through optimisation of in-bound, warehousing and processing activities in the Outlets supply chain.
In approaching the assignment, Berkeley first framed the problem, ensuring all relevant stakeholders understood the objectives; gathered historical and current data to highlight the issues; and defined the questions/scenarios to be addressed. The Berkeley team, partner Neil McClumpha and consultant Tom Parkin, then built a dynamic cost model to allow key drivers to be manipulated and the resultant impact on logistics costs to be quantified. Hands on scenario development with client team members gave them a good understanding of how all component parts of the logistics operation fit together and allowed them to explore and challenge relationships between variables. The team could then develop and test alternative configurations to see which interventions would have greatest impact on the overall logistics cost position.
The cost model was used to evaluate over 15 different hypotheses, quickly honing down to a top five that stood to have the most impact. With the M&S team so close to the emerging recommendations, they could easily and quickly establish what it would take to implement the changes and estimate the timeframes and resource needed. This had the added benefit of building momentum for the client team to move into implementation once sponsor approval had been secured.
In order to understand what was ultimately driving costs, it was necessary to first map the detailed logistics flows in each part of the chain and then to look for the subsequent linkages.
Berkeley started with the sales planning process, understanding first how excess product was identified from the main chain and how long it was likely to be held; for example, a consignment of cashmere cardigans committed to in Spring were unlikely to be sold until Autumn.
It was important to also understand the likely movements in average selling price (VAT increases, raw material costs etc.) as this was a key driver of volume, and how much physical capacity there was on the shop floor to shift the volumes being discussed.
In-bound logistics were then mapped to understand how much product was being moved in from overseas and how much was already in the UK. Warehousing operations were next, to assess how much stock was being held, for which selling season and in what form (i.e. hanging garments or boxed as these attracted very different handling costs).
Lastly, processing activity was mapped to understand how garments were priced, how individual store shipments were created and the labour required to manage those flows.
By developing a model that could integrate all the various elements of the chain, additional insights could be developed. For example, dynamically linking a view on stores capacity into the sales planning module highlighted a physical capacity constraint - the shops would run out of floor space - and led the team to consider developing an online channel. Also, by bringing together a view on current stockholding in various facilities, and the age of that stock, a plan to actively destock warehouses alongside the take-on of new excess product was developed. The team members with responsibility for specific elements of the chain could now see an integrated picture and make better operational decisions to minimise downstream impacts.
By using the model, M&S were able to easily tweak each of their key variables, individually and in combinations, to interrogate, challenge and shape their logistics operation over the coming years and to develop a plan to realise tangible savings.
Sometimes changes in one part of the business can have unintended consequences for another. This was exactly the case for Outlets, and it was down to the cross functional team that a major risk was spotted. The combination of a new logistics strategy and a move to SAP in the main chain business would result in changes to supplier contracts. The net impact of these changes was an earlier transfer of stock to M&S and a subsequent increase in stockholding costs to Outlets of some £1.6m in the year of contract conversion. Had this impact been missed, the overall savings opportunity for Outlets would have been cut in half!
The approach taken to developing the model was not a one off exercise, rather it equipped the Outlets team with a capability that they could use to operationally plan for, and adjust to changing business conditions. It also highlighted where greater coordination in decision-making was required between the different parties involved in supply chain operations. Often exercises of this nature are met with scepticism as to the validity of the analysis or the viability of the savings projections. In this case, through a process of co-development, challenge and joint exploration, Richard and his team felt confident and equipped to drive out the savings initiatives identified.
The work was completed in seven weeks. One cost savings initiative moved into implementation design within that timeframe. The other initiatives gained stakeholder approval at the conclusion of the project and a plan to save £300k is in progress for this financial year. Over the course of the next three years, that savings plan amounts to £3m. The modelling toolset developed is now actively in use to regularly plan and update sales and logistics cost projections, enabling the M&S team to more closely manage their operations than was possible before. The project paid for itself many times over and will continue to deliver benefits for Richard and the Outlets business in the years to come.
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