The complexity conundrum

Transcription

1 You can manage product complexity to increase profitability and customer satisfaction. The complexity conundrum By Brian Meeker, Dipen Parikh, and Manoj Jhaveri 54 x MM January/February 2009

2 We take innovation and new product development very seriously, and over the years have considerably expanded the depth and breath of our product portfolio. However, profit and overall customer satisfaction have actually decreased during this period. What are we doing wrong? Product complexity refers to the increasing number of product options a company offers. Over the last century, the product options pendulum has swung from Henry Ford s minimalist You can have any color as long as it s black to today s Variety is the spice of life excess. What s driving the increase in product complexity? Here are some examples: Increased globalization and more knowledgeable customers are pressuring companies to expand product offerings to fit unique requirements. Improved manufacturing processes and modular designs are enabling companies to target smaller market niches. Limited product-specific cost and benefit data is leading to a less effective mix of product options. There is a lack of effective product phase-out processes. There is an inaccurate understanding of customers needs and expectations. One common view is that more customer choices lead to higher sales and increased profits. However, based on our client experiences and extensive research in the automotive, telecommunications, office equipment, construction equipment, computer hardware and insurance industries, it is clear to us that a growing number of businesses today are not experiencing such results, and are actually seeing lower sales and decreased profits. (See Give Customers Products and Services They Value Profitably, March 15, 2008 Deloitte Consulting Point-of-View.) Too many product choices are in many cases confusing customers and resulting in lost sales, instead of increased satisfaction resulting in more sales. For example, two major automotive manufacturers recently reported that customers are confused by the growing number of vehicle options and frustrated when the exact model they want is not available. Additionally, the cost of managing product configurations increases with each increment of complexity. Many businesses have failed to recognize these negative impacts, as technological advancement has allowed them to efficiently produce more configurations. Some have attempted to tackle this problem. But without adequate product cost and benefit data, they often eliminate the wrong configurations. Although addressing product complexity is important, one should not conclude that offering more choices is always bad. In today s society, customers have come to expect a certain level of customization for many product and service categories. The goal should not be to stop providing customers with options, but instead to determine the correct mix of options that will increase profitability. SKU Rationalization Is Myopic Unfortunately, many companies have tried to address the negative impact of product complexity by applying conventional SKU (stock keeping unit) rationalization techniques. While effective in a make-to-stock environment, these techniques fall short in a make-to-order environment. SKU rationalization focuses on product manufacturing and distribution costs with low attention to product development, marketing, and aftermarket service costs. What s needed is a new and more holistic approach to managing product complexity that can be applied across discrete manufacturing, process and service industries. (See Exhibit 1.) The Product Complexity Management Process is a simple yet effective approach that facilitates the conversion of project, market, sales, cost and product information into crucial business intelligence. More than a one-time exercise, this fivestep process should be made an integral part of a company s product planning cycles to determine the most advantageous product mix. Step 1: Project Background The first step of a product complexity management project is to analyze the company s current situation and understand lessons learned from past complexity management efforts. The project team usually conducts interviews with key personnel in the business, and reviews past complexity management deliverables. Workshops are also held to identify the business units most impacted by product complexity and overall supply chain implications. The scope and objectives are then defined and hypotheses are generated. An example hypothesis would be: Revenue growth is flat because customers are confused by our large number of product options. The project team must also determine resource availability and the likely source and availability of data required to analyze product complexity. A MM January/February 2009 x 55

3 executive briefing Product managers are facing increasing globalization, rising customer expectations and growing competition. In what ways should they respond? One common approach involves expanding the product portfolio to offer customers more choices, leading to higher sales and increased profits. However, many businesses are not experiencing the expected results. The authors discuss this phenomenon and present a simple yet effective process to consider for managing product complexity. We believe integrating the process into product planning cycles could help maintain the correct mix of options and increase profitability. project schedule is then created to keep everyone marching to the same drummer. The next step involves obtaining a market view and internal view of product complexity. Typically, companies focus their analysis on a subset of products (e.g., their most complex product line). Step 2: Market View The market view includes performing a thorough competitive analysis and customer needs assessment. To conduct the competitive analysis, the project team must first define which critical industry metrics they want to focus on and what companies to benchmark against. For example, a computer manufacturer may wish to understand how many offerings its competitors have, the sales velocity and inventory levels for each of these offerings and the average profit margin per unit. Data and information can often be obtained from third-party consulting firms and industry benchmark reports. The customer needs assessment is critical in understanding what features and options matter most to customers, understanding how they will react if the feature or option is discontinued and estimating the level of product customization required. Smaller, iterative customer surveys usually work well in this case, as tackling too many product features and options in one survey does not permit drilling down to a significant level of detail on any particular aspect. Deeper customer insights can be obtained during each round of surveys, through increasingly pointed questions. Step 3: Internal View The internal view involves meticulously gathering product data such as sales invoices, unit volumes, supply chain costs, product development costs, marketing costs and aftermarket service costs from enterprise resource planning, customer relationship management, product lifecycle management, supply chain management and other corporate information technology systems. The data are used to understand the cumulative sales by configuration, fulfillment costs by configuration and average profit margin by configuration. Thoughtful use of spreadsheet and database applications can assist in integrating all product financial data and generating a full financial profile per unique configuration. Following are details regarding the theory used to understand and analyze the curves generated as a result of this exercise. Cumulative sales by configuration. Obtaining the internal view begins with understanding the concentration of sales across the full range of market offerings. Product manager intervention to shape the cumulative-sales-by-configuration curve is one strategy that can be used to improve profitability. In general, increasing the steepness of the curve can lead to greater productivity via standardization and economies of scale. In addition, shortening the tail of the curve can lead to greater profitability through reduced variation and operational n Exhibit 1 Managing product complexity Service Process Discrete Product complexity management Mobile phone service Cable service SKU rationalization Paint Chemicals Consumer electronics Appliances Make-to-stock Advertising Contract manufacturing Steel Aircraft Polymers Home computers Make-to-order 56 x MM January/February 2009

4 complexity. However, this is not always the most effective strategy. For example, in some market segments, customers are willing to pay much higher prices for desired uniqueness. Therefore, product managers should resist their initial reaction to reduce the number of product offerings. Instead, they should match the cumulative-sales-by-configuration data against the cost of fulfillment and profit margin data to determine the best overall strategy. (See Exhibit 2.) Average fulfillment costs by configuration. Another essential component of the internal view is to understand the relationship between fulfillment cost and complexity. In addition to supply chain costs, fulfillment costs include costs related to product development, marketing and aftermarket service. One method of shaping this relationship is broad-based cost reduction, which can enhance product-line profitability. An alternate strategy is to flatten the fulfillment cost curve. This can relieve the pressure to shorten the tail of the cumulativesales-by-configuration curve. (See Exhibit 3.) It is important to note that broad-based cost reduction and curve-flattening options are not mutually exclusive. The most effective strategy is one that takes into account both the internal view and the market view. Average profit margin by configuration. The third important aspect of the internal view is the average-profit-marginby-configuration curve. (See Exhibit 4.) Profit targets across all unique configurations should be developed based on pricing policies that complement product complexity strategies. Profit management begins with obtaining the average profit expectations from the corporate division. In most cases, the productline target profit should be set to capture additional profit as the cost and effort necessary to customize products increases. The average-profit-margin-by-configuration curve enables spot investigations of poorly performing configurations. In addition, pricing issues become noticeable, allowing product managers to investigate and deal with them. Step 4: Profit Improvement Opportunities By merging the information obtained during the market view step (competitor benchmarking data, customer consideration sets and so on) and internal view step (cumulative sales by configuration, average fulfillment cost by configuration and average profit margin by configuration), various profit improvement opportunities can be identified and ranked. During this step, it is critical to define a cost-benefit framework that is suited to the business and industry. For example, a consumer products company may focus on the economic trade-offs between contribution margin and sales velocity. Also in this step, the team develops conclusions regarding the various project hypotheses they formulated during Step 1. Step 5: Recommendations and Next Steps Finally, recommendations are developed by targeting the highest-value improvement opportunities. Here are potential product manager next steps based on these recommendations: Change current and future product offerings. Concentrate sales across fewer configurations. Revise new product development stage-gate metrics. Restructure supply chain operations. n Exhibit 2 Cumulative sales by configuration (notional) n Exhibit 3 Average fulfillment cost by configuration (notional) Cumulative sales Common product manager inclinations; sometimes right, sometimes not Average fulfillment cost Fulfillment costs rise rapidly as the number of product configurations increase Typical concentration of sales High concentration of sales, few offerings No concentration of sales Typical fulfillment cost Flattened fulfillment cost Broad-based fulfillment cost reduction Unique configurations Unique configurations MM January/February 2009 x 57

5 Modify product prices. Adjust the relationship between sales and service profitability. Align sales incentives with high margin configurations. n Exhibit 4 Average profit margin by configuration (notional) X% Average profit margin 0% Target profit margins should recognize the increased cost and effort associated with customization Problem configurations Profit absent pricing strategy Corporate profit expectation Target product-line profit Unique configurations Product Complexity Management Process Thoughtful application of the Product Complexity Management Process can lead to improved profitability, an optimized product portfolio, and increased customer satisfaction. It can also be essential to good decision making by confirming or refuting what conventional wisdom advises is the right thing to do. Consider these cases in point. The case of the multibillion-dollar global automotive manufacturer. It may be time to rethink your options. Problem: The company experienced difficulty managing its broad range of vehicle configurations, resulting in high inventory levels, slow sales velocity, strained dealer relationships and deep discounts. The lack of integrated financial data and competitor and market intelligence, along with divisions operating in silos all combined to hinder the company s ability to develop a balanced, market-driven product portfolio. Objective: Quantify the costs and benefits of the company s complex vehicle lineup, and derive an orderable configuration strategy that increases ongoing profit for vehicles in the United States. Findings (market view): Approximately 25,000 customers and 2,000 competitors customers were surveyed and 20 dealers and 7 regional managers were interviewed, to determine that the company s product offerings were more complex than its competitors and that the company lacked a regionally focused vehicle configuration strategy. In addition, managers and dealers reported that customers often configure vehicles online before visiting the store. More than 65% of truck buyers and 50% of sedan buyers configure vehicles online. As a result, customers focus on a particular configuration and price before visiting the showroom, and use the company s high degree of choice as a negotiating tool if the exact configuration is not in stock. More than 70% of customers reported spending what they expected or less on a new vehicle. Internal view. Creation and analysis of the cumulative sales by configuration, average fulfillment cost by configuration and average profit margin by configuration curves revealed that low-volume vehicle configurations created to address niches and increase profitability actually detract from total profit. In addition, some vehicle configurations contribute an extremely low level of profit, and total profit is actually driven by a small subset of the available vehicle configurations. Pushing highprofit, low-volume vehicles into the distribution network, without considering vehicle sales velocity, is a poor strategy that usually increases inventory. Profit improvement opportunities: To determine the potential areas of profit improvement, a cost-benefit framework was defined to ascertain economic trade-offs between contribution margin and sales velocity. The impact to both the company and its supply network was evaluated, and cost savings opportunities based on reduced offerings were calculated. Conclusion: A significant loss in sales revenue was attributed to increased levels of vehicle configurations. More really was less for this company. Customers were visiting dealerships, but couldn t find the car they had configured online. Dealers found it impossible to stock every possible configuration, resulting in lost sales and slow sales velocity. The solution was a product simplification strategy, which reduced the vehicle configurations by more than 60% while significantly increasing profit. The strategy was forward-looking and took into consideration the overall customer market strategy. Following are the key points: Realign the client sales and distribution model to execute a market-driven vehicle configuration strategy. Adopt an operating model for ongoing market-driven complexity management. Migrate eliminated vehicle configurations to higher average sales velocity configurations, allowing the company and its dealers to sell vehicles more quickly and with lower inventory. Focus on dominant decision-making attributes. The case of the multibillion-dollar office equipment manufacturer. Don t trust your intuition. 58 x MM January/February 2009

6 Problem: The company recognized its inability to determine the impact of product complexity for various product lines. It hypothesized that unnecessary costs of complexity could be avoided and overall profit margins increased by eliminating low-volume configurations. Objective: Conduct a product-line pilot study to develop a deeper understanding of the impact of product complexity, and either approve or reject the company s hypothesis. Findings (market view, internal view and profit improvement opportunities): The company s hypothesis was ultimately rejected. In this case, the wide variety of unique configurations offered to customers did not create unnecessary costs that could be reduced by simplifying product offerings. The combination of a modular product design, module interoperability, outsourced production and certain accounting conventions created a situation in which product costs were flat across product line offerings. This combination allowed the company to meet a variety of unique customer demands with tremendous flexibility, and enabled them to charge premium prices and earn higher-than-average margins on rare and unique configurations. In fact, these configurations contribute a significant portion of total product line margins. Simply reducing product offerings would compromise flexibility in responding to demand and could create the need for further price and margin reductions if discounting is used to persuade customers to purchase similar but not-exactly-what- I-wanted offerings. In addition, while this might reduce the number of supply chain touch points, it could also trigger supplier termination costs. Furthermore, bundling the functionality of existing separate modules into fewer, more capable new modules would generate additional product development costs. Based on the low average of module penetration discovered early in the project, it would also create many situations where the functionality desired would exceed customer requirements. As a result, some customers would look elsewhere because they may not be willing to pay a higher price for functionality that they don t require. Conclusion: Had the company acted on the original hypothesis, it would have cut the majority of its profitable configurations. The product complexity assessment not only helped it avoid a bad business decision, but also identified numerous opportunities to help improve product revenues and margins. Following are some of the high-value improvement opportunities identified: Improve price realization on high-volume configurations. Initiate a new supplier cost-reduction program targeting the highest-cost modules. Reduce order fulfillment lead times on a small group of high-volume configurations. Shift sales incentives toward high-margin configurations. Intuition Is Not Enough These case studies reveal that managing product complexity can lead to counterintuitive results. For the automotive manufacturer, complexity was eroding profits. But for the office equipment manufacturer, complexity was a competitive weapon. When it comes to product complexity, intuition is not good enough. What s needed is an approach that dissects all aspects of a company s product offerings and supports thoughtful product decisions. SKU rationalization alone is insufficient; evaluating the true costs and benefits of product complexity requires a more holistic approach that accounts for product development, marketing and aftermarket service costs. In addition, the approach must cut across manufacturing and service industries, and apply to both make-to-stock and maketo-order environments. The Product Complexity Management Process is a more comprehensive and effective approach for businesses struggling to determine the correct level of product complexity that will increase both profitability and customer satisfaction. n About the Authors Brian Meeker is a senior manager in the strategy and operations service area of Deloitte Consulting LLP, providing consulting services focused on lean product development in the automotive, industrial products, consumer products and high-tech industries. He may be reached at bmeeker@deloitte.com. Dipen Parikh is a manager in the enterprise applications service area of Deloitte Consulting LLP, and concentrates on consulting services involving new product development and product lifecycle management (PLM) for Fortune 1000 companies, including global PLM process design, lean process mapping, six sigma, project management, solution architecture, systems configuration and integration, training and overall implementation. He may be reached at diparikh@deloitte.com. Manoj Jhaveri is a senior consultant in the strategy and operations service area of Deloitte Consulting LLP, and he provides consulting services focused on product development, innovation and life cycle management across a wide variety of industries. He may be reached at mjhaveri@deloitte.com. Additional Reading Deloitte Research (2001), Creating Unique Customer Experiences: The Next Stage of New Product Development. Deloitte Research (2004) The Challenge of Complexity. Deloitte Research (2003), Mastering Complexity in Global Manufacturing. Prabhu, Ajit, Michal Locker and Phong Le (2008) Give Customers Products and Services They Value Profitably, Deloitte Consulting Point-of-View (March 15). MM January/February 2009 x 59