Toyota Examples of Mix Planning

Mix planning is an important process for companies that manufacture and distribute products to retailers in multiple market areas. For vehicle manufacturers, this decision is extremely important because of the complexity of a vehicle. This complexity creates millions of possible vehicle build combinations or variants. The objective of mix planning is to reduce the variants of each vehicle manufactured by several orders of magnitude, from millions to hundreds.

Mix planning is a process that is undertaken during major model change preparation. It can also be adjusted annually during minor model change and to a lesser degree during the model year. The model change mix planning is completed about 12 months prior to new model introduction, to enable the following to happen:

  • Marketing strategies for each region to be synchronized with product offerings
  • Manufacturing to fill the supply chain pipeline with parts
  • Sales regions to order vehicles to have in stock in time for new model introduction

Mix planning at Toyota deals with choosing the specific mix of vehicles that will be offered at sales regions across the country. The goal of mix planning is to carefully manage dealer-level product demand so as to enable stable production at the manufacturing plant. That also translates into stable orders to suppliers. In other words, the aim of mix planning is “to nip some of the demand variability in the bud” through careful planning. The associated upstream stability because of mix planning permits a focus on improved quality, cost reduction using kaizen, and ultimately higher value to customers that enables higher customer satisfaction and retention.

Studies suggest that Toyota cars offer approximately $2,500 in additional value to the customer compared with competing midpriced, high-volume cars. That additional value translates directly into a higher resale value that customers receive for their Toyota cars compared to most manufacturers in the auto industry. We attribute this higher value to variety reduction, variability control, improved visibility across the chain, and higher velocity. Thus, in order for the v4L strategy to be viable it must generate significant value enhancement to all players. We will cover this topic in later chapters, but first we focus on how Toyota does mix planning.

Mix Planning Objective

Mix planning at Toyota means that the planned variety offered in a sales area is chosen carefully to be primarily the 20 percent of product range that represents around 80 percent of the demand in that region. Thus, planned offerings in a region are frequently a small subset of all available product types or even of all product types offered in the national market. That simple decision enables synchronization of all activities in a region, from TV advertisements focusing on the specific colors and options available in a region to newspaper and periodical pictures and dealer brochures, all suggesting offerings that synchronize with the product available at the dealer. In addition, the smaller range means that most dealers carry similar products, thus both enabling customers to decide where to buy the car and keeping dealer margins competitive. Availability of the same set of products among dealers increases retail availability without the need for high levels of dealer stocks. Similarly, a focus on offerings with high-demand velocity also decreases dealer inventories and thus increases inventory turns. That is one of the reasons that Toyota’s average incentive cost per vehicle is typically about $1,000 compared to the $3,000 average for the industry.

A key risk to be managed in the selection of a subset of items is that that supply has to remain synchronized with current demand trends. Also, there is a natural tendency for the sales organization to attempt to justify why more is better. In other words, it is tempted to keep adding variants because doing so will help create incremental sales. That effort requires the need for thorough analysis of selling trends by product type and features, as well as monitoring of competitor offerings, in order to determine the optimum mix of variants. The key is that it is easier to add complexity or variants after the vehicle is introduced than it is to remove them. Therefore, it is important to start out by erring on the lean side and if necessary adjusting variants on a periodic basis after several months of sales history and trends can be evaluated. This method of adjusting mix during the monthly ordering process will be discussed in Sales and Operations Planning.

Complexity Reduction

Before mix planning can be undertaken, the product complexity needs to be reduced. That effort requires collaboration among design, sales and marketing, and manufacturing groups. The following is a summary of some methods that are used to achieve complexity reduction.

Product Planning, Design, Sourcing

Look for opportunities to use common parts across products (i.e., share radios). This step focuses on studies that suggest that over 80 percent of manufacturing costs are fixed at the design stage.1 So, preventing designers from adding variety when none is warranted is the first step. In addition, part commonality permits higher inventory turns for original parts as well as spare parts, production flexibility for suppliers and the assembly plant, and economies of scale in purchasing, design, and production.

Consider making high-volume options standard (e.g., if air-conditioning is sold in 95 percent of all vehicles, it should be made a standard feature). Such a step focuses on trading off the forecasting difficulties when choices are left to consumers against the enhanced value perceived when customers are offered standard features. For example, antilock brakes and other standard safety features may not be valued by customers if offered as separate choices but may well enhance the product preference if offered as standard. In addition, the forecasting of individual variants is often more difficult than forecasting the total demand for a product. This gain in forecasting accuracy as well as improvement in perceived value may well offset the lower margins because some features are discounted to customers who may not want them.

Eliminate options that do not sell well (e.g., if ashtrays are only ordered in 5 percent of vehicles, eliminate them as an option). This approach focuses on simplifying designs even at the cost of losing some customers in order to make demand more predictable.

Minimize parts that vary by option and color—for example, does the window washer nozzle on the hood have to match the color, or can it be black? In our example, supplier-part orders for the window washer nozzle will be kept standard even if customer vehicles vary by color. Because the same supplier component may be used in many car types, it is a great example of assembly postponement applied to stabilize supply while providing variety.

Attempt to source optional parts to local suppliers to shorten lead time. Such an approach focuses on decreasing safety stock by lowering lead time for difficult-to-forecast parts. In addition, because the forecast error for some options may be higher than for standard equipment, the lead time impact on safety stock inventory for optional parts is higher than for standard equipment parts. Thus, a more responsive supplier for option parts may well generate lower overall costs compared to an efficient long lead time supplier.

Design accessories that can be installed after the vehicle leaves the factory at a hub or at a dealer to minimize impact on the factory and supply chain. Such a practice moves some accessorizing tasks to the point of sale or close to the point of sale and permits last-minute customization for the customer. It is particularly relevant for cars like the Scion. The Scion is produced in Japan with almost no options or accessories. The vehicles are then kept in stock at the ports until the dealers submit an order, at which time the accessories are installed and the vehicle is shipped to the dealer.


Limit product offering for a market area. Vehicles sold in Europe and the United States should each offer a subset of products that best reflects local demand (e.g., manual transmission may be offered in Europe as an option but not in the United States). Such synchronization of products offered to local preferences makes demand levels more predictable and thus improves supply chain performance. In addition, such an approach increases the chance that demand can be satisfied directly from dealer stock, thus decreasing retail customer lead time.

Combine related options into packages (e.g., the safety package may include side airbag, stability control, and auto window wiper). Bundling of features permits the market segment as a whole to be targeted rather than individual feature choice. This process balances “up-selling” whereby customers end up choosing more than they actually need, with stability on the supply side. In addition, by converting products into, perhaps, three offerings (economy, deluxe, and luxury), with associated option bundles, customer choice is simplified and the number of variants sold at retail reduced.

Consider making high-volume options standard, not offering low-selling options, or both.

Mix Planning by Sales Region

After the complexity reduction activities outlined previously have been completed, the next step is for each sales division to work closely with its sales region to determine which subset of the vehicle mix will be the high-volume sellers in each region. This step is necessary because each sales region may have different demand characteristics. The following are some of the guidelines that are to be considered:

Limit stockkeeping units (SKUs). Determine which build combinations will be stocked by a sales region. A sales region within a sales company’s territory could be the southern region of the United States or Italy within Europe.

Analyze past sales, competition offerings, and local regulations to predict demand for future sales.

Use the 80/20 rule. The 80/20 rule identifies the SKUs that account for 80 percent of the sales. This should be about 20 percent of the possible SKUs.

Stock high-volume SKUs. Dealer stock should include only the 20 percent of the SKUs that represent 80 percent of the volume.

Target marketing campaigns to support mix planning by region. Synchronizing offerings with marketing plans permits customer preferences to be “guided” whenever feasible. For example, featuring the same subset of colors and features in print ads, TV ads, dealer showrooms, and dealer inventory increases the chances that customers will choose from the available colors and features and thus reduces the customers lost because of unavailability of special colors featured but not offered.

Manage demand. Provide guidance to dealers on ways to respond to demand for vehicles that are not in stock:

The salesperson can gently persuade the customer to change his mind and take one of the vehicles in stock. This is called “guided selling.” However, this technique could result in negative customer satisfaction. (Note: it is not necessary to sell a vehicle to every customer; sometimes it is better to lose a sale than to have an unhappy customer.)

Locate a trade with another dealer.

Request an order change from the factory. (This process will be explained in Dealer and Demand Fulfillment.)

Mix Planning Details

This example shows how the mix planning process is performed by the Toyota sales company:

Determine the volume of vehicles that is expected to be sold by region. For this example, assume that 10,000 cars—specifically, Camrys—are to be distributed across four different regions. The percentage sold in each region reflects the share of the national volume. With this market share, the volume by region is also calculated to ensure that the aggregate mix will be weighted accurately.

  1. Next break the planned volume into the volume of sales by vehicle model.
  2. This planned mix reflects marketing plans, production volumes, supplier commitments, expected competition and price points, demographics, and so on.
  3. Use data from each region to break up the total vehicle volume for a region into a composition by model. That data should be derived through collaboration between the sales headquarters and each regional manager.
  4. Take each car model and decide on the number of different variants that will be offered and the specific features of each variant. This is the most difficult part of the process, because it is extremely challenging for the marketing staff to limit the number of variants. Note that this example is an oversimplification. In normal cases, there will be hundreds of build combinations that must be considered. That is where the 80/20 rule will be applied. The result will be to select about 20 percent of the variants that will represent 80 percent of the volume.
  5. Decide on which of these variants will be sold in each region, and determine the mix of variants by region . The mix by region will then be used to calculate the volume of each variant by region during the monthly ordering process. (This process will be discussed in detail in Sales and Operations Planning.) Note that in this example not all regions will decide to order stock for all variants that were preselected by the sales division for the entire national market. However, they will still be able to make daily order changes or submit special orders for variants that appear on the national list.
  6. Finally, take each of these quantities and decide the colors that will be offered in each region and thus the specific quantities by color of each of these variants that is expected to be shipped to each region. Toyota processes reduce complexity and limit the mix sold within sales regions. The metrics for mix planning are the number of build combinations by region or country by model. Next we will examine how a mathematical model can be used to evaluate various mix planning strategies.

A Simulation Model

Although Toyota’s success may be proof that the 80/20 rule is valid, another issue that deserves focus is the empirical observation that SKUs that have lower sales volume have higher demand variability. In addition, the identity of these SKUs might not be the same from region to region. Thus, staying with the top 80 percent limits the variability seen by the plant; it also reduces inventories at the dealer. That reduces cost, improves forecasting, and further contributes to reducing variability. Moreover, it focuses selling effort on a small set of models and thus can drive demand in the right direction.

Given these different possible reasons for mix planning, we will focus on one such reason to understand details. The Appendix will provide a specific example; here we refer to the learning points from that example. Increasing product variety potentially attracts new customer segments to purchase the product and may thus increase the mean demand for the product. This increase in customer segments, however, may make the specific composition of demand for products in a period less predictable. Such a decrease in predictability may be understood (intuitively) as arising from the inability to predict the demand process for each customer segment.

So the benefit associated with attracting more customers to the product has to be balanced with the increased forecast error for individual products offered. In such a context, it may be better to offer a narrower range with more predictability. A more limited, more predictable demand stream may then enable a stable supply chain to be created, which offers the opportunity to increase customer value associated with a product.

A key question is, how much of the demand can be retained when variety is decreased? If, instead of 50 percent of the potential being captured, the demand drops to 30 percent, then it is worth considering how profitable this lowered variety is relative to increased variety.

What is the fundamental message of this model? Increasing product variety may increase demand forecast error because of difficulties in forecasting demand. It is the difficulty in understanding the composition of customer demand that creates significant forecast error—that is, it is easier to forecast aggregate demand but quite difficult to forecast the variety. Thus, careful targeting of customers and choice of product offerings can stabilize the system if the demand is not affected significantly. The trade-off between stability and sales volume has to be made prior to determination of the mix planning strategy.

Non-Toyota Examples of Mix Planning

A paper by Chan and Mauborgne on the “Blue Ocean Strategy”2 describes the process of pursuing differentiation and low cost. They describe a company that “generates cost savings by reducing factors that an industry traditionally competes on. Buyer value is lifted by raising or creating elements the industry never offered. Over time, costs are reduced further as scale economies kick in, as sales volumes increase due to superior value provided.” An example that is provided focuses on the choices by Casella Wines, an Australian wine company that entered the U.S. wine industry in 2001, when the industry had over 1,600 wine choices in the market.

Unlike existing strategies, Casella decided to focus on simplicity and on attracting new customers who were not traditional wine drinkers in the United States. The company thus decided to use one bottle type for red and one for white wines and offer only two types of each wine, simplify packaging, eliminate promotions, and go after nonwine drinkers with a fruity flavor. It eliminated all technical jargon from wine bottles and used simple, bright colors. Retail employees were encouraged by its ease of description to recommend it to customers. By eliminating a lot of the wine reputation–building costs faced by traditional wine companies, Casella focused on new tastes that made it easy to purchase, while simultaneously lowering production costs. At the same time, Casella managed to charge more than budget wines while growing the market significantly.

The narrowing of choices and simultaneous raising of satisfaction permitted a significant increase in the volume sold and enabled the company to emerge as the fastest-growing brand in U.S. wine history, surpassing the wines of France and Italy. In 2004, the company sold more than 11.2 million cases in the United States.

In the Conquering Complexity in Your Business,3 Michael George and Stephen Wilson discuss the impact of adding low-volume, less predictable offerings mixed with higher-volume products. If the low-volume products have greater variability relative to the mean, while the high-volume products have a lower variability relative to the mean, then offering all the products when their manufacture involves setups can decrease production cycle time efficiency for all products. Process cycle efficiency thus drops for all offerings when low-volume offerings are added in the presence of setup costs. George and Wilson suggest the need to identify the requisite level of variety that will optimize profitability by trading off the cost impact with revenue consequences of different levels of variety.

Titleist is the world’s leading golf ball manufacturer. The key to becoming a successful golf ball manufacturer is to achieve remarkable consistency in the plastic polymer used around the ball. Because all balls of the same type have to maintain equal performance to enable competition to focus on golfer ability, the company strives to carefully control quality. At the same time, there is the need to offer golf balls for a range of golfer preferences. The company thus has an appropriate range of golf balls but constantly works to keep the range as narrow as possible and still fulfill needs of golfers of all skill levels as the world’s leading golf ball manufacturer.4 Narrow variety, consistent quality, and economies of scale through appropriate pricing for performance all combine to enable Titleist to maintain its position as the leading golf ball manufacturer.

Reflection Points

How does increased variety hurt a company? When variety is increased while customer service must be maintained, the forecasting of demand and the adjustment of the supply chain become key issues. At the same time, greater variety permits products to appeal to a larger set of market segments whose preferences are now met by the new SKUs. If this new segment can be predicted and incorporated into existing processes, there is an opportunity to increase profitability. However, if the new market segments introduce fickle consumers and confuse existing customer segments, then adding SKUs may increase forecast error substantially, thus significantly increasing supply costs.

Toyota has demonstrated its strength as a learning organization by continuously refining its capability to manage vehicle complexity and the model mix sold in each sales region and by spreading these processes across the global organization. Specific examples are linked to the v4L:

Variety is selected by region to represent the popular mix demanded at a point in time. That permits wide availability of offerings among dealers for customers and thus keeps dealer markups low.

Velocity of sales is maintained by choosing to order for stock a few variants in each region. Those variants account for over 80 percent of the demanded offerings. That improves inventory turns at dealers and reduces days of inventory in the dealer lot.

Variability of sales is decreased by synchronizing sales and operations planning to focus on a few variants by region. Those choices are adjusted in response to observed sales. Thus, supplier and production quantities are stable in the aggregate.

Visibility of the planning process across sales and operations enables buying at the regional level. The push system of allocating cars to dealers enables fast turns and thus low dealer inventories. The thesis of the chapter is that optimal choice of the v4L enables Toyota to increase value.

The learning methods of Toyota are applied throughout the process to enable value creation, specifically:

Create awareness. The quantification of variability makes planners aware if they are not meeting the 80/20 guideline. In some instances, Toyota prefers to wait and see if the trends are permanent; for example, Toyota studies trends to see if mix changes are permanent.

Establish capability. Limiting variability where it occurs—at the dock in the case of the Scion, or at the design stage when it comes to limiting variety—makes the system more capable of handling variation.

Make action protocols. The quantification of the variety and the careful sequencing of planning steps, some top-down and some bottom-up, enables coordination.

Generate system-level awareness. The goal of mix planning is system-level optimization, where the system includes the customer and the entire supply chain.