Category Archives: Retail

Best Buy Experience? Not At Best Buy! Part I

It would appear that Best Buy is in trouble. And not just because Storefront Backtalk has been covering one problem after another on their web site about how Best Buy is “Making the Same Data Mistakes Again”, while being the latest example of a “Black Friday Fiasco”, and offering free “Wi-Fi Porn” to minors in its store. It is in trouble because they obviously cannot get a handle on their IT, despite trying to be a major provider of computers and electronics across North America.

But first, let’s recount the problems Storefront Backtalk has already told us about.

1. They’re still living in the “Wild West” and making the same data mistakes again.

How could an organization end up with “50 or so applications running on the cloud with absolutely no governance whatsoever”? That just boggles my mind. Maybe it’s the CTO in me, but I couldn’t even imagine 5 applications running untethered on the cloud. And not just because I’m not all that fond of clouds, which do have their uses when correctly applied, but because it doesn’t matter where your applications are — they still need to be managed, backed-up, and secured. It is, or I thought it was, just good old-fashioned common sense.

2. They sold product they did not have in their latest “Black Friday Fiasco”.

Not only did Best Buy take way more orders than it could fulfill for certain items on Black Friday, but it waited until a few days before Christmas to cancel those orders. Talk about a crushing blow to a customer, who has already been charged, and who thinks that special Christmas gift they bought a special someone is on its way. And talk about an insult when, instead of refunding the purchase, you send the distraught customer a Best Buy gift card. This is definitely a violation of trust. But even worse, one might be able to argue that this is a violation of the Uniform Commercial Code as the acceptance of payment can be argued to constitute a contract, which would mean the seller (Best Buy) would be obligated to transfer and deliver under Sec. 2301 or terminate with reasonable notification under Sec. 2309. The question is whether or not terminating almost a month later after accepting payment is “reasonable”. I’ll leave that to the lawyers, but note that as if this wasn’t bad enough, even in January, they cannot say what happened. This leaves one to surmise that they have some major IT problems, and won’t own up to them, which is not a good thing in the doctor‘s book.

3. It’s inability to implement simple Wi-Fi security resulted in a South Carolina store showing pornographic images on its large-screen TVs three (3) times in twenty-four (24) hours in it’s latest “Wi-Fi Headache”.

And one time, on February 12, the images were displayed at the Greenville location to children in the store for a full 30 minutes! And Best Buy has not offered a definitive explanation as to what happened. The story was changed from “two individuals accessed our store’s wireless signal to broadcast inappropriate content on a smart television display” which would require a wi-fi hack (unless they didn’t secure it in the first place) to “accessed a product display wireless signal” which would mean that just the “smart” TV’s were hacked to receive signals directly from a mobile phone. Further details indicated that “one of the signals in our store wireless system, specifically the one for product displays, was accessed”. But was that the case when Best Buy was “inviting people to come in and select whatever they wanted on their device and show it on the big screen”. Regardless of what happened, it looks like “store management didn’t have an immediate way of halting the porn displays” and that’s a serious problem. Especially when it has still not addressed how it will prevent this problem from happening again. But the worst part of this story is when a customer subjected to the images asked to speak to a store manager, the associate told him “You want to see the manager? You go get him. He’s over there.”. When it comes to customer service, how much worse can it get?

And that’s the real problem with Best Buy, as will be elaborated tomorrow in Part II.

Is Your Dumpster Full of Dollars?

And I’m not just talking about the significant savings opportunities that can come from optimizing your trash pick up with a good spend analysis, as discussed in SI’s recent post that asked [IF] You Know How Much Your Trash Costs You? An average retail chain will write of a lot of damaged inventory and discard it in the dumpster when, in fact, that inventory, if repaired, or, typically, returned in a timely manner, could result in significant dollars back in the retail chain’s pocket.

As pointed out in a recent post over on the Supply Chain View from the Field on “Reverse Logistics: What happens to all of those product returns you’ve been making, anyway?”, what typically happens with a return that could result in a credit to the retailer is that it ends up in many cases going into the dumpster even though, in many cases, the product is still good. This happens for a variety of reasons. The store manager doesn’t know that a return to the manufacturer will result in a credit. The store manager believes it will cost more to process the return than discard the item (or, if the store manager is lucky enough, sell it to a flea market). The store manager knows that there is money that is probably worth going after in the return, but has to use a new returns management / liquidation system that they don’t know how to use and can’t figure out on their own because it’s clumsy or ill-defined (like the SARS system that has been pushed down to individual stores by Home Depot and that could spell the beginning of the end). Or maybe they can figure out how to record the damage, get a pending credit, but lose the credit because they don’t process, and (bar)code the return properly.

Returns, which can often be refurbished, repaired, re-sold, or in the case of a NPI (New Product Introduction), returned to the producer/manufacturer within a certain timeframe for a full refund as per the contract, may not have the profit potential of a product that is not returned, but they still have profit potential and, most importantly, when properly managed, do not result in expense and loss. Proper reverse logistics and returns management, which is standardized, near real-time, and provides multi-channel visibility (as discussed in this post which brought you Reverse Logistics Tips from World Trade Magazine, significantly improves the bottom line and should be performed by every retailer and reseller.

For a few more tips, check out Rob Handfield’s tips from his post on “Reverse Logistics: What happens to all of those product returns you’ve been making, anyway?”.

It Starts By Remembering that an ARS is Used to Carry a LoAD, Not a Store. (HD Part V)

Last week we discussed the recent snafu made by Home Depot during a recent upgrade to its online website on February 1st that “Left Home Depot Customers Running in Circles” and chasing their tails due to incomplete planning and testing. We noted that, despite the fact that it was breaking news for some analysts and bloggers, it is not something Home Depot needs to be concerned about. However, as discussed in following posts, Home Depot does have some serious technology-related problems in the doctor‘s view — problems that it may not even be aware of which, if left unchecked, may only amplify as time goes on. However, as discussed in our last two posts, the problem has an easy solution, and it starts by rolling back SARS and retrenching to ARS at the Local Area Depots.

Done right, an Automated Replenishment System (ARS) is the foundation for next generation inventory management. Just ask any inventory management software vendor (including SYSPRO, that was reviewed here on SI in this post and this other post). However, done right requires that the implementation follow a few simple rules

  1. Forecasting at the item level is only done across a geography
    Trying to forecast item demand at the depot, and especially at the store, level is like trying to forecast the performance of an individual stock. It’s more or less impossible. For an item that moves erratically, a single purchase can shift the entire demand pattern. However, just like the performance of a broad mutual fund across an industry will be consistent over time, so will a forecast across aggregated demand across multiple Local Area Depots and the stores they serve.
  2. Forecasting at the depot level is only done across a short time span
    Again, while the demand for many depots will be predictable with reasonable accuracy, the demand at a single depot will not be predictable with reasonable accuracy over a long period of time. So, the more fine-grained the forecast, the shorter the term the forecast must be for.
  3. Forecasts can always be overridden and adjusted by the depot category manager
    No algorithm is intelligent. Not even close. An expert, who knows of a(n upcoming) promotion, change in local tastes or fashion, or trending feedback on product quality will always have the upper hand on certain items at the local level. Thus, the system should allow the local category expert to override each and every forecast and pull rule as circumstances dictate. As the rules get more fine-tuned, the need for this will decrease over time, but there will always be a special situation.
  4. Forecasts and Rules are reviewed and updated on a regular cycle
    As per our last few posts, the forecasts and rules assume at the minimum a predictable, if not a perfect, world — and the world is never predictable. The system will have to be adjusted as time goes on.

Furthermore, if the retailer insists on maximizing use of the system across each and every one of its locations, including retail stores, then the ARS must be restricted to suggest mode. In other words, there’s nothing wrong with using the rules engine and forecast models to suggest what inventory should be ordered, when, and in what quantity, but the order for any item must be presented for review by the appropriate category or department manager, and corrected if required. Thus, there should be human involvement at the end of each and every order cycle. If the category or department manager knows that only certain items have been presenting (potential) issues, the manager must be able to quickly review the suggested orders for those items, make any mods, and then accept the entire order for submission. In other words, if the system has been doing a good job on the widget category, the category manager shouldn’t be forced to review the widget category on every order, but should always have the option just in case she has an inkling. However, if there has been a continual stock-out of sprockets, the category manager should be able to up the order, and, if necessary, change the rule at the local level (subject to review of the depot manager or category manager if required).

And it must be extremely easy for anyone to report an error in inventory count or historical data at any location so that model, and forecast, is corrected as soon as possible. Without accurate data, the system will never work.

That’s the secret to a successful implementation of an Automated Replenishment System — don’t set it and forget it and don’t force it where it doesn’t fit. Monitor and adjust it continually, and as time goes on, it will get more and more accurate with less and less adjustment for any items with steady trends, leaving forecasters free to focus on fashionable or seasonal items in an effort to truly minimize stock-outs and maximize sales.

However, There Is Still Time To Turn Things Around. (HD Part IV)

In Part I, we began this series with a reference to a recent article in StoreFront BackTalk on how a recent snafu made by Home Depot during a recent upgrade to its online website on February 1st “Left Home Depot Customers Running in Circles” and chasing their tails due to incomplete planning and testing. While this was breaking news for some analysts and bloggers, given that it likely won’t even make a blip on Home Depot’s bottom line when all is said and done, for reasons discussed in the post, it isn’t something Home Depot needs to be concerned about. However, as discussed in the second post of the series, Home Depot does have serious technology-related problems in the doctor‘s view — problems that it may not even be aware of which are only going to amplify as time goes on. And these problems are very serious because, as discussed in the third post of the series, they are likely resulting in dissatisfied customers every day in every one of the 2,200 stores across North America. And when you consider that it would only take 3 dissatisfied customers per day per store (which seems entirely feasible in the doctor‘s view) to create 2,200,000 dissatisfied customers over the course of the year, the unnoticeable drops in the bucket become a rip current that could cause some serious damage.

So what’s the problem? As discussed in the last post, it is SARS, short for Storefront Automated Replenishment Systems, which, to the doctor‘s understanding, they have rolled out to the store level across each and every North American store over the past year or two. Advertised by vendors as the ultimate solution to stock-outs and lost sales, as the system is supposed to automatically place purchase orders and replenish inventory at just the right time to insure an item is never stocked out and that the optimum quantity is always on hand, it is sold as a retailer’s dream when, in fact, it is actually a nightmare in disguise. As explained in the last post, these systems only work in a perfect world, but there ain’t no perfect world, and they inevitably break down due to imperfections in the system, incompleteness in the knowledge, and inadequacies of the human operators (including programmers, administrators, and users).

You see, like traditional Automated Replenishment Systems (ARS), also known as Automatic Ordering Systems (AOS), SARS assumes:

  • Initial inventory counts are correct
    for each and every product in the store.
  • POS-based inventory updates are regular and correct
    preferably, on a regular, daily, basis.
  • Damaged merchandise is removed from inventory promptly
    and removed from the system just as promptly.
  • The replenishment model is accurate
    and takes into account weekly, monthly, and seasonal variations in demands
  • The world of tomorrow never comes
    because the model on which the inventory demand is modelled is supposed to repeat cyclicly with no change, ever.

But they are not Xanadu. And, in the doctor‘s view, the source of SARS is the same as that of the Kubla Khan because:

  • A significant number of inventory counts are always wrong … and this number only increases with time.
    There’s a reason retailers typically have all-night inventory counting marathons on a regular, often quarterly, basis. Damage, theft, loss, and human error results in a large number of products having an inventory count that is off.
  • Software is buggy and even the internet is not infallible.
    Errors in the POS system can result in the odd transaction not being included in the summary sent to the inventory system, the update file being cut off, or incomplete transmission. Plus, a poorly timed communication failure can result in the POS system thinking the transmission is complete when part of the file was lost.
  • Even if it is removed from inventory, it’s often not removed from the system!
    A junior associate may remove the item from the shelf, but forget to update the system. This will cause the inventory counts to get wildly out of whack over time.
  • The replenishment model is typically a randomly chosen best-fit model on available data.
    And depending on how much data is chosen, that model could change wildly.
  • The arrow of time dictates that tomorrow always comes.
    Next Monday will not be the same as this Monday. Next February will not be the same as this February. And as soon as an unplanned promotion occurs on an unexpected item, something wildly different will occur.

In other words, at the store level, SARS does not work — at least not in an automated fashion. Thus, if Home Depot wants to turn things around, or at least insure that things get pointed in the right direction before it needs to turn things around, in the doctor‘s view, it needs to (partially) abandon SARS at the store level and go back to ARS at the (local) distribution centre level where, when done properly, ARS can be tuned to work like a charm. How? That will be discussed in the next post.

Is Your Retail Supply Chain Ready for the Holidays?

A recent article over on SupplyChainBrain on five key lessons e-Commerce merchants can learn from the 2010 holiday season identifies some key supply chain requirements for a successful holiday season that all retailers should keep in mind.

  1. Holiday Shopping Starts Early
    It is now stating well before Black Friday, so your outbound supply chain should be ready to ship as soon as Halloween is over. This means that you should already be starting to build up inventory for products expected to be in high demand.
  2. Cyber Monday Matters, but don’t ignore the rest of the week.
    Shoppers are looking for deals all week. Be ready for a consistent demand.
  3. CyberWeek is big, but the following weeks are bigger.
    Orders increase as shipping deadlines approach. Be ready for a lot of orders, and a lot of outbound shipments, as close to your shipper’s cut off dates as possible.
  4. Average ticket declines are not necessarily a bad thing.
    Especially when volume increases, which is the current trend.
  5. Vertical Markets Matter
    Apparel, Shoe, and Toy sellers increased market share, and may be on a trajectory to do the same this year.

In other words, you need to

  1. Prepare for early demand
  2. that will increase steadily until the shipping deadlines
  3. when you will have to be prepared to ship a large amount of product very quickly and deliver on time.