In 2004 Chris Anderson from Wired Magazine wrote a somewhat controversial article titled “The Long Tail.” The basic premise of the article was that our consumer culture and economy have a growing appetite for unique products and services. To be successful and attract buyers, retailers need an ever-growing selection and variety of items to sell. The desire for specialized and niche products exponentially stretches the tail of the demand curve. The article synthesized the essence of online marketplaces, where consumers are increasingly able to pick products based on ever so specialized and fragmented tastes and wants. Every shopper has experienced the endless choice in the long tail when searching for things to buy at Amazon, for example. Plentiful categories and variations, including oddities such as bacon-flavored dental floss and a desktop pillow for those hung-over days at the office, amongst millions of other specific articles. Chris Anderson went on to write a book on the theme in 2006, titled “The Long Tail: Why the Future of Business Is Selling Less of More.”
Since Anderson’s article in 2004, there has been a lot of debate regarding the validity of the long tail as a workable business model. It’s fair to say that only a few internet distribution companies can afford to base the entirety of their business in the long tail model. However, even click-only retailers, such as Amazon, do not live entirely in the long tail. Amazon uses the long tail to attract buyers with variety, making a profit when retailers sell a product through their virtual marketplace. Amazon also employs the web store to capture data, to know what buyers are clicking on and looking for online. Approximately, only 7% of the items sold by Amazon are in the head of the curve. The remaining 93% fall in the long tail and help collect the data that is critical to the company’s success.
Furthermore, we should not think of the long tail only as a business model but as a business reality that happens to both “click-only” and “click-and-brick” companies. It’s not exclusive to retailers either. When we consider the diversity of customers and products combined, we find that every business has a long tail. Long or short, companies can use the long tail to their advantage, like Amazon, or allow it to become a burden. If not managed, the complexity from thousands or millions of SKUs will destroy the free cash earned at the head of the demand curve. The fact is, every business needs a strategy to deal with the long tail.
The tricky question is how conventional retailers and manufacturers can keep up with the level of portfolio expansion and specialization required to succeed. We know that they are not all prepared to adopt the same business model as Amazon. The problem is exceptionally hard for manufacturers, considering the logistical and operational challenges to design, produce, and support so many products. To survive and thrive, they need to learn new tricks and approaches to portfolio expansion, learning from data analytics, and new sourcing models to avoid detrimental complexity.
Fortunately, there are many examples of companies that have transformed themselves by learning how to manage long-tail complexity. Retailers such as Kohl’s and Best Buy, are braving the trend by combining physical and online stores. Others, like Sears, Macy’s and JCPenney are struggling, going out of business or closing stores as sales decline. The digitally transformed know that the long tail can be healed and used to bring about profitable growth. Manufacturers like Seiko, Scania, and Bosch Rexroth are a few examples of companies that use product variety to their advantage.
With more than 650 million SKUs in their offering, Amazon is burdened by complex logistics, engaging and retaining retailers and understanding customer and market trends to the highest degree. The cost of complexity is there, but it doesn’t grow as fast as the long tail. They can efficiently add thousands of new products every day while keeping operating expenses under control. For manufacturers, though, it’s a different story. The slight growth of the long tail induces an extraordinary amount of complexity cost under the surface. Every additional product brings new components, manufacturing assets, people, and support costs. Complexity is not as friendly to manufacturers as it is to retailers.
But variety sells and most traditional industries that resisted portfolio expansion are now growing the long tail, including European car producers, for example. While the major brands used to carry an average of 100 to 150 car models only ten years ago, they are now offering an average of 250 to 300 models. Nowadays BMW has more brands (BMW, M, Mini), series variants, body styles (SUV, cross-over, sedan, coupe, convertible) and drivetrains (electric, hybrid, PEV) than ever. Mercedes-Benz and BMW are two of the most prolific brands in the US in terms of variants.
Manufacturers must learn how to manage and grow the tail without adding to the cost of complexity. In other words, they must balance portfolio expansion with scalability. Every variant added to the portfolio has to contribute to the overall bottom-line profitability. Offsetting the losers with the winners don’t always work! The tolerance for freeloader products (the low profitability ones) gets challenged by the fact that companies are targeting markets of one: every product and every customer count.
To become masters of complexity and capitalize on the long tail, retailers and manufacturers must change in at least three ways. First, they need to embrace digital transformation, improving skills to predict customer behavior, and knowing real-time the financial impact of adding to the tail. Second, companies need to be better at new product introduction and portfolio management to measure the effect of expanding the offering, governing, and quantifying the actual cost of complexity of every transaction. Lastly, manufacturers need more modularity and commonality in their product lines. They also need to outsource more finished products to suppliers or vendors.
Businesses display different abilities to manage variety and deal with its inherent complications. Some don’t recognize or measure the cost of carrying too many variants and merely react to market needs and internal problems. Others estimate the cost and attack complexity using a systematic approach. Based on how companies deal with the long tail opportunity and the costs of complexity, we can divide businesses into four categories:
1. The cost-cutter: Most companies are drawn into the long tail incrementally and, only when the symptoms become too burdensome, they launch an attack on complexity. These companies are good at continuously pruning the overhead associated with external complexity. This category includes those who apply ABC (Activity Based Costing). Archetypical example: Ford.
2. The lean practitioner: Some companies restructure internal processes to minimize complexity from inception. They recognize and deal with both causes and symptoms from within their four walls. These manufacturers make a great effort to standardize processes (engineering, purchasing, sales) and reduce variation (production lines, warranty) within their organization. It includes practitioners of Lean and Six Sigma. Archetypical example: Toyota.
3. The simplifier: Companies that measure and recognize the problem with uncontrolled complexity. They work hard to contain product and customer variety and are always pruning the long tail and segmenting the business for increased focus on the vital few customers and products. It includes many users of the 80/20 business process. Archetypical example: ITW.
4. The master of complexity: Complexity governance is at the core of these businesses. They are savvy users of big data analytics. They embrace product variety and expansion by partnering with other vendors and channel players to create unique offerings and develop efficient commercial ecosystems. They use true product profitability or the individual product P&L as a guide to expand the offering. Archetypical example: Amazon.
The first two types (cost-cutter and lean practitioner) focus on the symptoms of complexity, while the third type (simplifier) centers on the causes of complexity. The fourth category (master of complexity) is concerned with creating profitable variety and distinguishing between detrimental and beneficial complexity. They are the prototypical long-tail professionals and not limited to online retailers at all.
We call masters of complexity many manufacturers that have developed modular product line architectures to create profitable variety, including Scania, Rexroth, Seiko, and many others. The toy company, LEGO, has become a synonym for good assortment and modularity. When referring to Scania, for example, we can say that they use a “LEGO approach” to build and sell trucks.
Moreover, if we look at value creation to shareholders under the lens of stock price appreciation for the four archetypical companies, we can see a significant difference amongst them. For five years alone (October/2014 to October/2018), using the SP500 index as a comparison basis, Ford and Toyota underperformed the index by 16% and 10% respectively while ITW and Amazon outperformed the SP500 by 60% and 392% respectively.
The comparisons may not be entirely fair since these are different industries, but it helps illustrate the performance delta that simplifiers and masters of complexity can achieve over time. Profitable variety is a significant contributor to growth and value creation.
ITW manages the long tail by segmenting businesses continuously and having them managed by market-focused business units. Segmentation is essential because each ITW business unit has unique demand curve characteristics. For instance, for any business unit, the head of the curve may represent a lot more than 7% of total revenues, like in Amazon’s case. Additionally, the long tail may not be as valuable as it appeared to be before segmentation, once managers consider all the costs associated with the tail alone.
Amazon creates variety to attract more buyers and vendors every day, offering a highly visible and desirable online marketplace to transact. The company has minimal operating costs to be divided across the millions of products. It’s the ultimate scalability model. The long tail of the demand curve is profitable for Amazon, while the head of the curve is hugely profitable.
Scania, the Swedish truck maker, also uses product diversification to give customers options. It allows Scania to sell trucks into low-volume applications, such as logging and mining. The long tail for Scania consists of products that use similar components to high-volume truck models that are in the head of the curve, albeit assembled in unique ways. The cost of complexity is under control because of Scania’s modular product line architecture.
Modular architectures and vehicle platforms are enticing to automotive companies. Recently, Ford has accelerated its efforts to simplify. In 2018 it announced that it would revamp its North American product line by dropping most low-volume sedans while focusing on pick-up trucks and SUVs. While they are not changing their product line architecture yet, this is a positive step towards dealing with the causes of internal complexity.
Toyota has also embarked on a program to consolidate all its car models in 2012, down to three vehicle platforms, known as Toyota New Global Architecture (TGNA). The new architecture will increase the sharing of components among vehicles and reduce the number of models by 2020. The modular assembly program will reduce costs in several ways and will be more LEGO-like. The introduction of smaller manufacturing lines, for instance, is expected to decrease initial plant investment by approximately 40% compared with 2008 levels. Toyota is starting to tackle external complexity and going the way of simplifier companies.
Besides governing complexity and creating smart variety, simplifiers, and masters of complexity use data in unique ways. They go beyond reporting and financial analysis, with unique model-based analytical tools using the Pareto Principle as a framework to develop insight and value from big data. The inexorability of imbalances in the numbers and the clear separation between vital few and trivial many are forcing algorithms to learn and to incorporate this familiar experiential model. Time after time, big data analytics keeps pointing to the fact that only a few customers and products create most margin dollars and growth.
Data analytics, coupled with Pareto thinking, enables masters of complexity to work comfortably in the long tail. They integrate different customer experience elements to transform data into valuable insight, helping achieve the trade-off between variety and scalability. Granular insight leads to better management of individual products and customers when using the long tail to attract new customers.