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Try our demo. The way we know if the new stores are bringing new sales is by assessing the same store sales of the older locations. Same store sales is calculated by adding the total sales for all of the stores that have been operational last year and subtracting this amount from the total sales of the same stores this year, then dividing the result by the total sales of same stores from last year and multiplying by to get the percentage.
This one will measure the total revenue growth and will include all stores from this period month, quarter, year.. This will measure the comp sales growth like-for-like growth and will include only the stores that were open and trading during the same period last year. This could mean that part of the revenue of Store 5 is actually driven by shifting customers from store 2 and store 4. It could also mean that Store 5 is very closely located to Store 4. More information and customer data will be needed here to asses the situation and the feasibility of opening Store 5 at that location.
When you generate the reports you will look at both, the total like-for-like sales as well as the like-for-like sales by location. If the retail business is having a Like-for-like growth, then it means that the business is in growth mode and is still acquiring new marketshare.
In this case opening new stores is the go-to strategy to sustain this growth, reach more customers and drive out competition.
Same store sales growth depends on how long the businesses has been open and the market situation. For example a new business is typical to show a high LFL growth in its second year of trading, that could reach the double digits. However, it is also important from an economic point of view to understand exactly what the figures are measuring.
From a macro-economic point of view, the like-for-like measure of sales is not actually much use. It is largely irrelevant how those sales are split between stores that were already open and new stores.
Similarly, economists like to know the total cash amount consumers have spent — which means including the amount spent in VAT for example. Indeed, the best macroeconomic measure of sales is one that includes as much as possible — including online and other multi-channel methods of sales. One challenge for the statistical authorities is to make sure they are capturing changes in the way retailers sell and ensure that they are measuring all types of sales.
Like-for likes are useful, from the landlord perspective, as a general input in the covenant assessment process — to get a rough feel for the performance of occupiers or prospective occupiers — but it takes a lot more to nail-down the actual health of individual players. The growth of multi-channel retailing is clearly muddying the water.
The problem now is differentiating between branch network dependent internet sales and pure internet sales relatively rare where no branch network exists or branch networks demonstratively have no impact on the specific internet sales recorded equally rare. Where goods are paid for via the internet or other non-shop channels but are collected or delivered from branches; or where sales are dependent in any other way on the existence of a branch network showrooms for example , transactions are branch dependent.
Branch dependent sales, and only branch-dependent sales, should be reported in like-for-likes. This issue is of particular relevance in property markets because of the prevalence of turnover rents. If branch network dependent internet sales are not fully reported, branch turnovers will inevitably be understated. Allowing internet purchased returns at any branch causes similar problems. The problems stem from both the wide variability in what actually constitutes LFL and also from a lack of care in the interpretation of LFL figures that often leads to misuse of the metric, especially in media reporting.
Yet if they are so confusing what is the point of LFL? Generally speaking, the purpose is to allow for a fair assessment of underlying trading performance at individual retailers without taking into account store or space expansion — both of which can have a major, and exceptional, impact on sales growth. While LFLs are useful in the context of individual retailers, they are much less helpful when exploring the wider retail picture.
Indeed, LFLs should categorically not be used to assess the overall health of the retail economy. Overall health can only be assessed by looking at total spend or sales as this gives the best indication of aggregate demand in the consumer economy; comparatively, LFL sales reflect only a part of consumer spending. Theoretically it is possible to have very robust overall sales growth while LFL growth is strongly negative.
Whether at a retailer or overall level, it is critical not to use LFLs in isolation. It is also important to understand that there is not one standard definition of LFL. Different retailers have different policies and performance always needs to be assessed in light of the specific accounting treatment behind the LFL calculation. With the proliferation of transactional channels, it could be argued that the LFL measure is now essentially redundant.
In actuality, this increased complexity probably makes understanding LFLs more, not less, important as, at a retailer level, they can play a key role for decision making in areas such as store consolidation and optimisation.
So, LFLs will likely remain a key measurement tool for retailers. But never should they become the be-all and end-all. In retail, as in other businesses, numbers are just the result — a kind of shorthand for all the strategising, decision making and execution.
They certainly provide a useful guide and steer for future planning, but number gazing does not drive businesses forward. Only innovation, planning and hard work can do that. Like-for-like sales while apparently simple are open to multiple interpretations.
Which stores are to be included is the first statistical issue. LFL sales require the store to have been open over the period under consideration, but stores are seldom static with extensions, refurbishments, re-merchandising, etc.
There is then the time period involved, for example sales for a week or month compared with sales for an earlier week or month and linked to this is the elapsed time of the earlier period, thus week on previous week sales or week on same week previous year sales. The ways of allocating sales to stores may differ from firm to firm; for example with different treatment of internet click and collect sales, of coupon sales, of staff discounts, of VAT, etc.
Within a firm these statistical issues are likely to be consistent, so evaluations of individual stores and inter-store comparisons within a firm can be meaningful. But the statistical issues often are very different in different firms so inter-firm comparisons and sector level figures resulting from aggregation lose meaning.
Interpretation of LFL figures are affected by issues that are external to the retail sector, sectoral changes and also internal strategic issues in the firms. External factors include changes in the retail timetable, for example the timing of Easter and the day of the week on which Christmas Day falls, and also big differences in weather. These all affect the interpretation of LFL sales, at all levels of aggregation.
Sector changes affect interpretation through different levels of inflation being present at the compared time periods this is particularly the case with year-on-year comparisons. The way that channel structure evolves also affects interpretation with shifts away from store based selling, which is the basis of LFL calculation, having the potential to reduce the total of store based sales even within an overall growing market. It is perhaps at this level that LFL has most meaning.
Within firm LFL can be a useful measure but with the current confusions, when using it for sector level figures and inter-firm comparisons there is often much ado about nothing. Nobody could argue that this information is not useful, in principle, to the management team.
When broken down by volume and value and compared against like-for-like footfall, it enables the business to establish the key forces driving the performance of its estate. As an internal measure, it has always had intrinsic merit, as long as the retailer has established rule sets to accommodate refit programmes, expanded space in stores etc. Without an industry standard, retailers have understandably been creative in how they chose to declare like-for-like sales publicly.
Mezzanine floors and loyalty card redemptions spring to mind as two examples in recent times that gave rise to inflated like-for-like figures released externally, and, before that, petrol sales when supermarkets began installing forecourts. Beyond that, online sales present a whole new area of potential confusion over the metric, particularly if such sales are attributed to local stores.
To the outside world, the value of disclosed like-for-like sales figures is diminishing, simply because all too often they neither provide a fair reflection of underlying sales, nor do they provide a fair comparative base between retailers.
Internally though, where the company standard has been defined and regularly reviewed, it will still deliver powerful insight and so remain. After all, it is easy to open new stores, as the big supermarkets are doing, and claim that overall sales and market share are booming. Retailers who are growing their store estate particularly quickly may well claim that LFL sales are not a fair measure of all that their business is doing, but the City is rightly suspicious of retailers who refuse to give LFL sales figures.
The standard definition of LFL is to include stores that have been open for more than 12 months, although some retailers take a more conservative view and only include stores that have traded a full year at the start of their financial year. But the devil is in the detail and the debate is about the detail….
But it is stretching the definition of LFL to include store extensions in LFL, even though the store has not changed and the major supermarkets are particularly culpable in this regard. It is absurd, not least when underlying LFL sales are weak, for supermarkets to claim some sales growth by effectively including new space in the form of extensions. This policy of including store extensions in LFL should be banned. A more tricky point is when stores get a significant investment in store refurbishment, with the express aim of improving sales, but as the more significant the investment is in reformatting the store, the more disruption there will be during the revamp process, in terms of losing sales, in the round it is probably fair to include refurbished stores in LFL.
But one of the bigger issues is whether LFL sales should include online sales, as the fast growth being seen in online retailing is bound to flatter the figures. Indeed it is getting hard to know where the boundaries lie. After all, if customers research a purchase by looking around a store, but then order online for their convenience and pick up the order in-store is the purchase a store or online order?
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