©iStockphoto.com/ t.light How to Escape the Variant Jungle Software Support for Successful Variant Management Schuh & Company Complexity Management Complexity Manager – The Ultimate Software Tool for Managing Variants Hands-on planning and control of variant diversity A large number of cases consistently show how cumbersome it is to handle multiple product variants. A high and increasing amount of variants affects many processes, leads to ever increasing costs and incredible variety and complexity of data. Creating an urgently needed transparency over the existing product variety appears to be impossible. Where to start? Is there a leitmotif which may provide orientation and may lead to a solution? Re-assessing and streamlining the existing product variety constitutes a major challenge, which often intimidates employees. This is the situation where doubters and preservers argue for the “status quo” as there is no time available to conduct the complicated task of reducing the existing product variety. Moreover, these people advise against the reduction of product variety due to fear of lost sales stemming from customer disappointment. These issues are highly dangerous in the medium and long run. Companies, that are (still) performing well, need to be proactive and look ahead. Action, not reaction is the name of the game. Profit needs to be prioritized over revenue. The ‘leave it as it is’ attitude does not only postpone the problem, it worsens it. Instead of decreasing the problem, the problem grows in size. Finding the starting point is the most difficult part. This is exactly where appropriate tools and methods help to alleviate the anxiety for streamlining the product variant diversity and to find the leitmotif leading to a reasonable level of product variety. The two-perspectives approach to variant management In at least 100 projects conducted throughout more than 20 years, two perspectives have been proven to be helpful in analyzing product variety: external and internal complexity. Figure 1: External and internal perspective on complexity due to product variety 2 Thread M22 Surface: smooth Length: 2.8 inch Length: 2.8 inch Length: 3.2 inch Length: 5.1 inch Thread M20 Surface: fluted Surface: angular Surface: angular Pictures taken from an advertising folder of Mann+Hummel Figure 2: Product example “Oil Filter” The market perspective (external complexity) Describing the product based on customer-relevant options and features provides an overview of the number of variants that need to be taken into consideration for the product. Here, the central questions are: What product configuration does the market require? What does the customer want? What is unnecessary? This perspective ensures that the product range is not restricted as far as the current market requirements are concerned. Instead, extremely low running variants which do not contribute to operating profit are simply removed. The basic principle is “As few variants as possible and as many as necessary.” The external complexity can be quickly made transparent by using the Complexity Manager Module F (Feature Tree). The definition of variant-related features and their options, as well as rules on combination restrictions due to technical or market restrictions, are quickly incorporated. These features can be automatically generated by importing data directly into the complexity manager. The restrictions can be either imported or they can be defined by “point and click” in the software. Figure 2 shows the parameter values of an oil filter that are important from the point of view of the customer, meaning, these parameter values are recognized by the customer. Without combination restrictions of individual feature characteristics, this small table alone would lead to 324 possible oil filter variants. However, due to technical reasons and the realization that certain combinations are not required by the market, specific rules can be defined regarding combination restrictions or mandatory combinations. Rules are defined using logical AND (▪) or OR (+) chains. 3 Figure 3: Overview of combination restrictions and mandatory combinations When analyzing existing product families often times data is already existing which can be directly imported or which needs little adaptation to be transformed into an importable format. A popular way of displaying data is the matrix form. Here combination restrictions are labeled by an “x” (see red fields in figure 4). This matrix display can be easily imported by the Complexity Manager and the shown combination restrictions are automatically created. Based on these restrictions, which can be either manually created or imported via the matrix form, the number of variants in this example is reduced to 26 oil filter variants. The required data for visualization is entered when the rules are defined. Figure 4: Overview of combination restrictions shown as matrix form 4 Figure 5: Visualization of the external complexity (market) in the feature tree On the basis of this data, the Complexity Manager provides numerous possibilities of simulation, for instance: Changing the number of variants by partial replacement, addition or removal of features Creation of different scenarios (“What if…”), simulation and their evaluation Calculating the probability of occurrence of certain variants due to sales forecasts (assists in the early recognition of possible low- or nonrunning variants) ABC analysis based on actual sales figures (separates the ‘wheat from the chaff ’) The Company View (internal complexity) After evaluating the market view on the product including questioning every variant, a range of products has been created which needs to be actively offered to the market. Taking the internal perspective is supported by the Complexity Manager Module V (Variant Tree). The main question which has to be asked about the internal view is: How to get the demanded product variety flowing through the factory as efficiently as possible? The guideline here is “As few parts as possible and as many as necessary.” As the following figure shows, required parts variants can be assigned in the system on a step-by-step basis and in accordance with the assembly sequence on the production line. Comparisons of cost and price Figure 6: Variant tree visualization using the assignment of parts to product variants 5 Of course, corresponding data can also be imported via the interface in Module V. The overview in the completed variant tree (see example in figure below) provides information about parts that are the biggest variant drivers. It highlights the part of the production line were the actual variety occurs and shows which assemblies and parts are suited to be pre-assembled and which should really be removed from stock (for variant optimization purposes). Furthermore, in case new products are planned, early warning is given of ‘imminent’ parts variants and quantities, which proved to be particularly useful. This also supports material requirements planning. To go one step further, it is also possible to derive information in order to plan needed manufacturing resources, for example, the necessary investment in tooling can be determined. A clear and early oversight over the amount of parts variants leads to the necessary amount of tool variants which have to be procured by the firm or by a supplier. Parts Figure 7: Variant tree of an oil filter 6 variants, which differ significantly with regard to their design, will probably demand different tools resulting in high investment. Variant planning, enabled and conducted by the Complexity Manager, supports companies in evaluating the need of tool variants already during product planning and, if necessary, to search for alternatives to avoid high investment costs. Results of a separately conducted complexity cost analysis can be considered in the Module V. According to the cost-by-cause principle, higher costs are allocated to rare and exotic variants while fewer costs are allocated to standard variants, since the latter easily pass through the value chain. Creating this cost transparancy largely supports the decision wether to introduse a new variant or not. The following issues, among others, may be simulated: Implications of substituting variants with standard products along the assembly sequence. Potential restructuring of the assembly sequence in order to optimally place the variant creation point. Decision support to what degree a product shall be assembled in one production site when several alternative production sites exist. Implications due to the elimination of single variants and options from the feature tree on part and product variety in the variant tree. Prediction which additional part variant demands a new tool variant and which part variant can be produced with an existing tool. Summary During the numerous applications, when Schuh & Company applied the Complexity Manager, it showed that transparency over the variance of an existing product family as well as the variety of a planned product program can be achieved with greatly reduced resource input. structure has already been made, these expenditures cannot be regained by an ex post elimination of existing “unnecessary” variants. However, there is cost savings in every product manufactured in the future. It has to be made very clear that the implementation of a consistent variant management is greatly beneficial without any exception. However, as is well known, taking the first step is the most difficult part. On the one hand, the existing “variant jungle” appears too complex, on the other hand, there is hesitation to reduce the product offering and in turn fear to lose market share. Since the problem of variant diversity will not be solved without effort, quick action is urgently needed. By applying appropriate methods and tools like the Complexity Manager Module F/V, one will easily come to realize that first partial successes will show quickly and that the light at the end of the “variant jungle” will emerge. In the end, variant management is even fun. These are our experiences gathered together with our customers in more than 20 years of successfully applying the Complexity Manager. Moreover, it showed that avoiding variety in the first place is far more important than reducing existing variety, since the cost reduction potential is far higher in case of the former. When integrated early in the planning phase, variant management helps firms to prevent unnecessary investments in infrastructure, tooling, and machinery. By integration of sales forecasts, low-selling and non-selling variants can be identified, avoiding unneeded development costs, investments in tools, machinery and infrastructure. In this way higher effects on cost savings can be achieved. The effects of minimizing an existing product program are far smaller compared to avoiding “unnecessary” variants in the first place. Nevertheless, the effects are not insignificant either. However, since the investment in tooling, machinery and and infra- Figure 8: Effects of avoidance of variants 7 Module PM: The Meaningful Complement to Analyze Data From the Modules F and V Module PM provides further opportunities to analyze data, which is created and processed in the Modules F and V. The direct connection to MS Excel enables an automated creation of diagrams for illustration purposes of the results. An essential component of Module PM is the integration and consideration of planned life spans / life cycles of single variants. Which variant is valid when? Which variants are going to be created next year? Which variant will be taken out of the portfolio soon? These are essential questions which can be answered by a precise and chronological variant planning. Module PM offers, for example, the possibility to display the variant diversity that will be valid over the next two years. The feature tree graphic shows life cycles of the single variants and displays them clearly arranged in a GANTT chart (see figure 9). Figure 9: Feature Tree and overview of variants’ life cycle 8 Figure 10: Validity of options during life cycle In case of already existing data regarding the validity of single variants, the data can be displayed and clearly arranged. The validity of single variants consequently affects the validity of single product features and product options. Which option has to be provided when? Which option will be phased out when? Module PM derives this information from life spans of single variants and answers these types of questions in an extended option statistic (see figure 10): What is true for life spans of variants is also valid for their bills of material. In the list of parts and components, Module PM calculates the life spans for needed parts and components based on life spans of single variants. This is shown in figure 11: Figure 11: Validity of parts during life cycle 9 Figure 12: Example of line charts for illustrating sales volumes (past and forecast) Moreover, this figure clearly shows that information regarding the quantity of necessary parts can be automatically generated from the sales figures of the variants. Dependant on which figure is entered (annual sales figures, or sales figures per life cycle), Module PM calculates the respective demands for parts and components. The variants which have been sold up to now provide concrete sales figures in the respective periods. However, how can future sales or sales forecasts be considered? How will the sales figures of a single variant develop in the future based on its previous sales figures? Which framework conditions can be expected? Module PM provides an answer by offering the possibility to include forecasts in the extended option statistic. For variants where no previous values exist, Module F/V provides the possibility to enter probabilities. In the case that previous sales figures exist for a variant, estimation formulas can be entered in Module PM that calculate future forecasts. By directly exporting this data into Excel, the results can be displayed in a chart. This is illustrated with the following example of the length and the surface of the filter (in this example forecasts values are used from 2012, see figure 12): Moreover, Module PM provides the opportunity to filter variants, for example based on sales figures/ quantities or life spans/validities. After entering the respective filter criteria, all changes adapted accordingly. Figure 13: Defining the period to check for valid variants 10 Figure 14: Extract of Feature Tree: Valid variants in defined period The variants can be filtered according to date, for example, April 2015 until September 2017. The Module PM directly displays the respective feature tree for the valid variants in this period, which in turn, affect part variants. Summary Module F/V contributes significantly to differentiating necessary from less necessary variant diversity. Furthermore, it answers the following questions: Which variants are really demanded by the market? Which part variety is necessary to provide the demanded variants? How high are the expected necessary investments in tooling and equipment? Once the necessary level of variant diversity is defined, Module PM offers the feature which displays at what point single variants have to be scheduled. By providing the timeline and life spans of single variants it is now possible to plan specific periods from a variant perspective and analyze sales quantity during that period. Firms are supported to focus on the important key issues especially with regard to ramping-up and singling out products. Receiving information when specific variants with the respective components, sales quantities, and tools are needed, significantly releases the burden of product complexity and helps to control it. Product-specific variant planning based on Module F/V is now complemented with a time specific variant based on Module PM. Contact Product Variety Management Visit our website for more information: www.schuh-group.com Joerg Starkmann CEO, Schuh Complexity Management Inc. Phone: +1 770 614 9384 joerg.starkmann@schuh-group.com 11 Company Schuh & Company focuses on providing solutions and methods for managing the ever increasing complexity of today‘s enterprises, products and processes. With this approach, the company was established as an implementationoriented problem solver in the industry. Today the company consists of about 40 experts committed to ensure your company’s success through their work as strategy and organizational consultants, as well as management coaches. Schuh & Company is headquartered in Aachen, Germany, with subsidiaries in St. Gallen, Switzerland (since 1991), and Atlanta, GA, USA (since 1997). Offices Schuh Complexity Management, Inc. 3625 Greenside Court Dacula, GA 30019, USA Phone: +1 770 614 9384 Fax: +1 678 730 2728 E-Mail: info@schuh-group.com Schuh & Co. GmbH Campus-Boulevard 57 52074 Aachen, Germany Phone: +49 241 51031 0 Fax: +49 241 51031 100 E-Mail: info@schuh-group.com Schuh & Co. Komplexitätsmanagement AG Langgasse 13 9008 St. Gallen, Switzerland Phone: +41 71 243 60 00 Fax: +41 71 243 60 01 E-Mail: info@schuh-group.com www.schuh-group.com