Desperate for profits, retailers reinvent inventory strategies

Desperate for profits, retailers reinvent inventory strategies

Proper supply chain inventory management is necessary to the success of a company.  Arthur Peck, CEO of Gap, explained that he has “zero patience for a lack of operating discipline” when his managers inappropriately organize their retail supply chain inventory.  Late last year, Gap experienced a serious conflict with their inventory systems.  Their poor supervision of inventory resulted in high operating expenses and an excess amount in inventory.  This surplus has led to undesired markdowns in price in the beginning of 2018 and will continue to damage Gap’s margins.

 

A significant majority of these faulty supply chain inventory levels can be attributed to the volatile demand behind digital retail.  Prior to the surge in online sales, companies could get a solid grasp of in-store demand and effectively plan out their brick-and-mortar inventory levels to meet that demand.  Thus, supply chain inventory levels would be updated on a consistent basis with a solid idea of the size demand coming their way.  With digital sales however, a product may have to get shipped to various different locations before being transported to its buyer.  Also, there is more unpredictability of which product will be sold and to where, so retailers must be cautious with their inventory levels.  And of course, with e-commerce increasingly becoming the more popular choice of distribution, managers must be on edge regarding how to appropriately combat inefficient inventory levels.

 

In order to avoid high inventory and storage costs, many retailers have shut down stores, moved products to a universal warehouse location, and even kept lower on-hand inventory levels to accommodate sporadic e-commerce.  J.C. Penny did just this and increased their online SKU count by 50% in 2017.  The retailer also utilizes inventory from their physical stores to fulfill online orders.

 

As e-commerce continues to bolster in popularity, and as the Amazon effect persistently negatively affects retailers, I think supply chain managers need to make quick decisions and achieve inventory levels that allow for quick distribution but also maintains a workable size of inventory.  With more inventory, the retailer can ship more products out quicker, but will face unwanted operation expenses and margins.  Yet, with a smaller inventory size, the company will experience a minimized amount of product availability, so delivery time will be slow.  Achieving a happy medium between the two previously mention scenarios should yield the supply chain manager with the most ideal results.

 

I personally think companies should sacrifice product availability rather than maintaining high inventory levels.  I mainly believe this because having higher inventory levels hinder your financial statements.  With higher costs of goods sold along with increased end-of-year inventory and other expenses, public companies may look less desirable to investors as their earnings per share will be negatively affected.  Accordingly, I think sacrificing speed of delivery or quickness of transferring inventory is the correct move for retailers to make.

 

Question to consider: As we discussed in precious postings, I would be curious to see in the future how AI directly affects supply chain inventory levels.  Could artificial intelligence accurately forecast online demand and improve inventory methods?

 

 

Sources:

https://www.supplychaindive.com/news/retailers-reinvent-inventory-strategies-profits/518354/

 

https://www.cnbc.com/2017/01/05/the-retail-apocalypse-summed-up-perfectly-in-one-chart-commentary.html

10 thoughts on “Desperate for profits, retailers reinvent inventory strategies

  • March 27, 2018 at 9:14 pm
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    In oder to forectas sales the first thing needed is data, that is why is so hard to forecast online demand; because there is not enough data abailable. Companies have been selling online for the past 5-10 years, so based on those few years it is very hard to forecast demand; which leads to a hard inventory planning.
    The good thing is that online sales are increasing over time, so in the future companies will be able to have that data. But in the mind time I think is better if they have more inventory than less; because right now what customers want is to have their items shipped and delivered as soon as possible. That is the key of succes for online shopping; Amazon is the perfect example. So, even though this will not look good in the financials of the company they would be able to satisfy their customers, build a relationship. Then, once they start having more data and be able to do better sales predictions, this need of holding too much inventory will be gone.

  • March 28, 2018 at 3:47 pm
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    I think your suggestion about the impact AI will have on inventory planning is a good one. Certainly, as companies compile more and more data on inventory management in the e-commerce era and embrace the power of analytics, an effective combination of the two will be very valuable to those who employ it. I think another aspect where that ability will play a role is in the effective aggregation of inventory management. The trend towards regional warehouses with less inventory kept on hand, along with frequent coordination between brick-and-mortar stores to provide for customers, means that companies have to find a way to balance inventory management on an aggregate level, a regional level, and a store-by-store level. This is definitely a more daunting task than past supply chain management, where managers could boil down inventory needs to simple forecasted demand in one store. Hopefully, the rise of AI and proper implementation of big data will lead to resolutions.

  • March 28, 2018 at 4:19 pm
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    With e-commerce brimming and in-store sales declining, a majority of companies have had to rethink their inventory and supply chain strategies to keep up with the change in customer purchasing trends. Lack of data could be a possible reason for the inability of these companies to manage online demand. However, these companies could collect/buy data from a wide array of companies to get a better sense of their demand. I was talking to one of our admissions officers recently and she told me that the way the university manages its yield is by buying data from SAT/Collegeboard. This data tells the university about the other places students have applied to by looking at the universities they have sent their SAT scores to, amongst other things. Once the university has the data, it hires consultants to determine the yield. Therefore, even though the university might accept fifty students into the scholars’ program, it expects only twenty-five or twenty-seven of the accepted scholars to actually enroll at the university. This sounded like a very precise process to me and it works every year. Therefore, if companies can collect data from other agencies such as postal service companies to determine how many retails companies (competitors) are selling products through some specific channels in a period, it can not only help them determine their inventory levels but might also help them figure out some possible locations to market more products based on competitor sales. Moreover, with the help of this data, companies can identify gaps where they can market more products and increase sales which will ultimately help them determine inventory levels. Here is an article that provides a detailed description of how most universities are able to use data to manage their yields. https://www.mbacrystalball.com/blog/2016/08/22/enrollment-management-strategies-colleges-yield/

  • March 28, 2018 at 8:23 pm
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    This article (http://www.bain.com/publications/articles/good-sales-and-operations-planning-is-no-longer-good-enough.aspx) talks about how it is no longer enough for companies to have “good enough S&OP). With consumers getting used to better quality service and more convenience, S&OP has to be exceptional. I think retail stores are starting to learn this, and that’s why they are trying out new strategies. In the long-run, they will benefit for not settling, but instead for pushing the limits to stay competitive in the market. I am curious to see how the different inventory strategies will turn out for the companies, and if they will start using them or if they will have to keep trying out new strategies.

    • March 29, 2018 at 8:44 am
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      I think that it is inevitable that companies will not settle on their current inventory strategies. Just like in any market, things are constantly changing; nothing is different for the retail industry. I believe that all firms that want to survive will take the time to analyze the ever changing market and push the limits to stay competitive in the market. By doing so, this is best for everyone involved, specifically the customer. By constantly competing and innovating, firms will make their processes more efficient, resulting in higher customer welfare; the cost of products may be lower. All in all, it is mandatory that companies continue to push their limits and not settle if they want to survive and advance. If they do not, they will share the same result as Toys R Us.

  • March 28, 2018 at 8:43 pm
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    I agree that it will be very interesting to see how AI will influence the retail business. The article below discusses how giants like Walmart and Amazon are acquiring tech start-ups as a way to advance their artificial intelligence development efforts. I think that all retail stores will need to use AI in order to adapt to the more e-commerce centered world we live in. I think those retailers that are successful in adapting these new technologies will be able to survive and those who don’t may fade away over time.

    https://www.supplychaindive.com/news/artificial-intelligence-AI-retail-future/518192/

  • March 28, 2018 at 11:41 pm
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    After reading Lauren’s post about Nordstrom’s new local store I think it is funny you mention the benefits of having less inventory and how companies should be moving towards this strategy. Nordstroms has identified this supply chain tactic and is trying to act on it to decrease costs.
    In terms of AI and supply chain management I definitely think inventory will decrease because companies will be able to extract information from large datasets, analyze trends, and forecast relative numbers of the exact products/goods needed. Companies will be able to optimize orders in real time and adapt to changes made by competition or created by disruptors.

    https://medium.com/@Aera_Technology/ai-and-the-evolution-of-demand-forecasting-147dd4e783aa

  • March 29, 2018 at 12:40 am
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    I think it is very fascinating to think of a future where companies have no stores and fully operate online. Many people today would say that that is unrealistic, but with the demand for online purchasing in both retail stores and restaurants growing every year it is hard to predict a horizon for this growth. It is true that right now many stores do not have enough data to fully analyze how efficient their online businesses are, but with the right organization, I think that many stores will find that many retail stores like gap will find it more profitable to eliminate their stores and got almost, if not fully online. This will be especially the case as technology becomes faster and easier. When a company is able to cut the shipping time of an order to a day or less for everyone such as Amazon is predicting they will eventually be able to do, many consumers will find it unecessary to every go into a store again.

  • March 29, 2018 at 8:31 am
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    What’s interesting to me in regards to the increase in e-commerce is the extreme amount of selection companies need to have in order to have a successful online business. Many consumers go online to find exactly what they are looking for, then check out. In fact, a company like Wal-Mart, who is starting to get into their own e-commerce platform through Jet.com, has over 25,000 different items. With the extreme amount of selection, in addition to the fluctuating demand like you mentioned, companies such a Gap will absolutely run into operating issues. They have to find a way to utilize their own big data to be able to forecast properly across all their segments.

    Fortunately, Gap can utilize AI to do this. An artificial intelligence machine has the ability to detect problems in the supply chain and report it to a manager instantly. However, a human can teach a machine that this anomaly is normal, and thus the machine will not report such a problem again and instead focus on alternative issues. Such machine learning makes demand forecasting more and more accurate for supply chains.

    The issue for Gap is that humans must be able to use the technology effectively. Making sure the data that the artificial intelligence is receiving is clean and accurate is essential because AI can incorrectly learn information (which can ruin the infrastructure). Thought leaders need to find a way to effectively use and monetize this data so that they can get closer to an error-free and profitable company.

    https://global.factiva.com/redir/default.aspx?P=sa&NS=16&AID=9VIV000400&an=JBT0000020180127edc10000a&cat=a&ep=ASI

    “Digital Transformation: Three Skills Demand Managers Must Have”

  • March 29, 2018 at 9:31 am
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    The clothing industry is certainly a tough area to produce a reliable forecast. On one hand, clothing is considered a necessity, making the demand consistent and fairly inelastic. On the other hand, there are an immense number of producers of clothing and every producer takes advantage of a certain market share. Some people use clothing to make a statement about their financial stability or buy clothing to keep up with current trends. Others go out to find the most utility in what they wear, valuing functionality over anything else.

    Producers such as Zara, which have coined the term “Fast Fashion” have turned to exploiting trends in generating large revenues. Zara operates a handful of suppliers and intermediaries, allowing them to turn over a new product in as short as 2 weeks. As mentioned, predicting store vs online sales can be a challenge. One solution could be measuring website traffic as a cue to initiate production so that goods would become available shortly after being viewed. Another problem that retailers face is show-rooming, where consumers will go to the store to pick out and look at an item only to order it online for a better price. I think that eventually AI will measure store and website traffic to eventually generate a reliable sales figure for nearly every industry.

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