Next Generation Product Complexity Management Are You Ready to Use Digitisation to Manage Product Variance? 2 Next Generation Product Complexity Management Contents

Next Generation Product Complexity Management Are you ready to use digitisation to manage product variance? 2 Next Generation Product Complexity Management Contents

Executive summary 4

Benefits of complexity management in the new digital world 5

Product complexity management has to involve the global value network 6

Leverage technology to control product complexity 9

Become world class with product analytics 14

Start today! 20

3 1. Executive summary

Product architecture and platform manage- that product complexity is not managed By doing so, those organisations use ment are in many industries a proven agile enough to meet the mentioned PLM analytics tools to strive to perfection way to reduce product complexity in an business environment. in product architecture and platform effective and efficient way. Particularly in management. In our product complexity maturity study automotive and manufacturing it is the we focus on the dimensions of strategy, Within this point of view we want to outline core of the product strategy and therefore product, supply chain, production and the trends and challenges of manufac- a critical capability. technology. The key finding was that the turing companies in this field and also Leveraging carry-over parts, analysing existing IT tools and technologies are give a viewpoint on the possible levers to product data, managing the variants and merely used for organising the product address these and to optimise product restructuring the supply chain accordingly portfolio, but not for driving decision complexity management. Our approach is leads to a significant reduction of customer making in the field of product complexity easily understandable and addresses the lead time as well as product and engi- management. In order to create significant key obstacles to overcome. neering cost. However, product business value with the increasing product complexity management today faces data available, new approaches to multiple disruptive changes along the optimise and manage product complexity value chain, such as global manufacturing are possible. Companies that are “Insight- networks, growing competitive pressure, driven complexity optimisers” have already diverse local customer demands, rapid understood how to manage an integrated technological innovations and new product architecture that is operated with regulations. Customers expect person- established processes and governance alised products quick and locally available functions across the whole value chain. at any time with the expected quality. In addition they use analytical methods Global organisations are often not able to optimise their existing product portfolio to fulfill all of the demands with the same and new product developments in a degree maturity. One of the reasons is structured and insights-driven way.

4 Next Generation Product Complexity Management 2. Benefits of complexity management in the new digital world

Organisations in every kind of industries Several companies already perform at a Global organisations could benefit are faced nowadays with an increasing high level in the field of product complexity tremendously through an integrated individualisation of customer requirements. management, especially in the automotive product architecture and platform To fulfil this expanding demand, compa- industry. The modular transverse matrix management in the fields of service, nies react by enlarging the number of platform of Volkswagen is only one quite production and engineering. Based on product variants. This automatically leads popular example. But today’s question our experience, a world class product to higher complexity, which the compa- is: to what extent do they consider current architecture and platform management is nies have to cope with. This becomes and upcoming industrial key challenges able to realise significant benefit effects. especially visible in the automotive and like sustainability, globally distributed manufacturing sector, but also exists for value creation networks, market volatility example in energy and utilities. Thus, and, most notably, the cross industry’s organisations need to learn, how to digitalisation with its cyber-physical manage the balancing act between production systems? While conventional fulfilling the market needs regarding complexity management is able to individual functionalities on the one hand manage product complexity locally quite and reducing internal complexity to save well, a new approach is necessary to costs and time on the other hand. also address the growing complexity and digitalisation of the value network.

Up to -90% customer order lead time Up to Up to Seise digital opportunities -20% Reduced steering effort +40% Improved process efﬁciency process service costs Reduced idle and lead time ef ciency Reduced risks and quality costs Number of variants Process complexity Reduced supplier and sourcing costs Ability to serve global markets

Up to Up to -30% -30% engineering product costs costs

5 3. Product complexity management has to involve the global value network

Product complexity management is a an increased effort in material planning. During the product series conception challenge, which affects the whole value The goal of complexity management here rising complexity implies smaller and more chain and therefore needs a comprehen- is to structure the product requirements expensive purchased parts. Besides, sive solution approach. Companies and enforce a reuse of existing solutions. rising amount of components often leads continue to globalise and implement new to higher stocks and therefore rise in The same principle takes place in the variants of their products to spur growth. working capital. The vision of product design stage of the value creation. While As a result, the global value network complexity management in this phase is product complexity causes increasing R&D coordination, covering the idea to develop common architecture compo- costs and provokes development of new generation, requirement specification, nents to facilitate an integrated portfolio parts, product complexity management design, product series concept, sales, management across all product families takes care of early definition of carry-over realisation and assembly and after all and brands. parts and establishes maturity concepts operations and maintenance, is more and for components. Thereby, existing compo- A major negative effect of increasing more challenging and therefore drives nents can be easily identified and parts as product complexity in the sales phase is product complexity. well as subassemblies are prepared for the rising complexity of demand forecast Within the requirement specification reuse as much as possible in order to the large number of variants has led to reduce reinvention costs.

Figure 1: Global distributed value creation network

Fully integrated architecture and platform management and a standardised idea-to-market process

Requirement Sales Realisation / Operations & Design Product Commercial SOP Idea speci cation series concept offer Assembly Maintenance

6 Next Generation Product Complexity Management and cannibalisation of products and product complexity management has to of product complexity simplifies through brands in the different markets. Managed integrate the product view by all means standardisation of service processes and product complexity should simplify from engineering through manufacturing lowers the failure rate of parts, due to the demand forecast and could even ease to service in order to always have the reduced number of variants. the training needs of salesmen. With a right view of the product. Standardisation To address the requirements towards managed central sales configurator the of production processes is a consequent an integrated product complexity salesman and the engineering department benefit and eases the delivery of persona- management while keeping the has easy access to all data needed. They lised products locally at a reasonable price. value network performance high, can use it to describe and manage the Also operations and maintenance are a comprehensive, but flexible and market offering internally and externally to affected by rising product complexity. If technology-based solution approach significantly reduce interface problems as not managed well, effects can be higher across all stages of the value chain well as customer lead times. installation times or space requirements is needed. Further, increased product complexity than actually needed. In addition the causes small lot sizes and high tooling service technician has to know each part variety which complicates the realisation details of a load of variants. For opera- and assembly process. Therefore, tions and maintenance the management

7 8 Next Generation Product Complexity Management 4. Leverage technology to control product complexity

The importance of the drivers for product Globalisation leads to a globally distrib- in sourcing, producing and delivering, but complexity will intensify rapidly in the next uted value creation network with new on the other hand also requires an increas- years. Strong internal and external influ- customers, especially from the emerging ingly complex and locally focused value ences will force organisations to improve markets. As we all spoke about global creation. their product management substantially. markets a lot in the past, this has now Another trend affecting the complexity of It is necessary to identify the implications become a reality, especially in Asia. Most products is the technological develop- of these trends and to adjust the current of the European automotive players now ment in both, process and product tech- view on product architecture and platform operate production or even development nology. In the field of process technology management proactively. The develop- sites from there. On the one hand this the “Internet of Things” enables multiple ments can be structured with the product provides a large number of opportunities complexity diamond, which contains five interdependent dimensions: competition, customer, globalisation, technology and regulations. Figure 2: Product Complexity Diamond

Today’s competitive environment is characterised by increasing pressure and market volatility that affects the entire value chain and therefore also the Competition requirements of products and services. Differentiation through quality and additional service has become a major 2 1 competitive factor instead of the lowest Regulations price. 3 Also the customer demand for perma- nent product or service innovation and Technology Product individuality is becoming increasingly Complexity important. Companies often answer individual customer requirements with an increasing number of variants. A German premium automotive OEM, for instance, has planned 10 to 15 new production Customer ramp-ups within 20161. Agile management of variants is crucial for these industries, right here and right now. Globalisation

1 http://www.automobil-produktion.de/2014/06/exklusivinterview-mit-norbert-reithofer-bmw-das-ist-ein-ziemlicher-kraftakt/

9 possibilities for autonomous demand With those developments, it is obvious, in automotive and manufacturing indus- planning or production through cyber- that on the one hand new technologies, tries. With this observation, we wanted to physical supply chain systems.2 Also, the global value creation, strong competition find out how successful companies connection of the physical and digital and higher customer requirements need address those challenges and how they world through sophisticated communi- adjusted regulations, e.g. to enable handle product complexity management cation, identification and localisation entering new markets. On the other hand today. Therefore, we compared the technologies complicates the organisation market-specific conditions affect product maturity in five industries: construction but can also bring up new opportunities, regulations, such as country specific legal machinery, white goods, power generation if intelligently applied. Likewise, those new restrictions for product security reasons equipment, transportation and automotive technologies are the basis for product or product data protection which leads to in a research study to get a clear picture innovations. Thus, attractive products are different variant types for different regions of the as-is situation.3 We analysed several quite complex and have to fulfil multiple or even countries. companies of each industry regarding customer requirements towards their usage of product complexity All in all we see these drivers currently “traditional” customers and the “young” management levers such as strategy, getting more and more intensified and tech-generation. product, supply chain, production relevant for global organisations, especially and IT tools and technology.

Figure 3: Degree of product complexity management maturity in covered ﬁelds by industry

Criteria (excerpt) low medium high

Product complexity is addressed in the corporate strategy Strategy Product complexity is emphasized in corporate communication

(Re-) use of parts, components and processes Product Use of modular product structures Shift of product differentiation towards end of the value chain

Supply Product portfolio-oriented supply chain segmentation Chain Degree of supplier-integration into value network Supply chain ﬂexibility, e.g. production oriented supply hubs

Production segmentation and ﬂexibility of needed operating Production resources Integrated / simultaneous production engineering

IT-Tools and Technology Product management big data / analytics capabilities Integrated PLM / PDM decision making processes

Automotive Transportation Power Generation Equipment White Goods Construction Machines

2 Holler et al.: From Machine-to-Machine to the Internet of Things, 2014 3 Capgemini Consulting Research 2015

10 Next Generation Product Complexity Management Anchoring the topic in the corporate In order to manage product complexity it What we have seen across all focused strategy is important for external and is important to apply a product specific industries is that IT tools and technology internal recognition and emphasising impor- supply chain and integrate data flows are barely used to support product tance. However, according to this field across company borders. The construction complexity management. Neither the study, the integration of product com- machine as well as white goods industries deep integration into PLM and PDM plexity management into the organisa- show just a few relevant initiatives like software is a standard nor the use of tion’s strategy is just partly done in the flexible stockings. Even fewer intentions of analytics. White goods manufacturers construction machines industry, whereas supply chain integration and segmentation and transportation providers at least most of the white goods companies were identified with power generation have implemented telematics services coupled their position clearly with product equipment manufacturers, while trans- extensively, but don’t leverage big complexity reduction targets. Also power portation companies show at least partial data or analytics. In this field also the generation equipment companies integrate supply chain integration and segmentation automotive sector does not take much product complexity management clearly initiatives to manage product complexity advantage out of the structured use of IT into their strategy – in comparison to as part of their nature. Automotive firms tools and analytical technology as a lever transportation providers who nearly do not have already mostly aligned their supply for product complexity management. This consider this at all. The highest maturity chain with their product complexity field is most immature overall. of strategic consideration of product management and use it as a strategic Although we find multiple examples, complexity management was stated in asset to fully involve suppliers in the early where companies already use digital the automotive sector making it a clear phase of product development itself into technology in a product complexity forerunner. their product architecture and platform context (see digital best practice processes. Naturally, products are the most important solutions), we also see a tenor of fear lever for influencing product complexity, Parallelisation of production process towards using it as a standard in a i.e. construction of carry-over parts, activities, segmentation of production lines structured way to support objective modular product structures, postponement and more flexibility by using operating decisions in a governed way. It is also of product differentiation to the value material are levers to support product obvious that while the automotive chain’s end or using platforms as a com- complexity management within the industry is again a pioneer and paves munal part structure. The construction production processes. Construction way, other manufacturing sectors lag machine industry shows intentions of machines manufacturers intensively behind. But the use of technology is the modularisation only in the subareas of consider these levers and tend to make key success factor for the future and is product design whereas white goods production processes more flexible, already a differentiating factor on the way manufacturers are carrying out modu- whereas a slightly lower degree of maturity to becoming a world class market leader. larisation and platform architecture in this field is realised by white goods Everyday data is created, attached and initiatives as a standard. More than half of organisations. Power generation and changed. Data insights through technology the power generation equipment compa- transportation equipment firms are not bring new impetus in this exciting topic, nies and a major part of the transportation yet integrating production processes where not everything has been settled equipment firms also show clear modu- and product development processes in yet. Where and how to use technology larisation and product architecture con- terms of product complexity alignment. naturally depends on the specific cepts. However, the automotive industry The automotive industry is again the situation, but it definitely brings new has implemented the highest maturity of top player in this field and stands out by and unexpected benefits. So get rid of complexity management within the applying complexity principles accordingly technology pessimism and find out how product design using product architec- in production. the future can look like. tures and platforms including cross- product family and cross-unit collaboration.

11 12 Next Generation Product Complexity Management Digital best practice solutions

Design Solution Finder Sales and Service Release Communal Parts Analyser A digital solution finder helps to manage Configurator In order to visualise interdependencies product complexity within the design To tackle the sales complexity the gross between components or product families, stage by searching existing component- of companies have implemented a sales a communal parts analyser helps to solutions easily through an engine-based and service release configurator. It enables make similarities or even communalities keyword-search across the whole sales representatives to define a scope transparent. By this, the latest product company and partners. With the solution of a requested or anticipated business component data is consolidated in one finder, the degree of re-use of e.g. and customer activity by selecting and consistent graph database to create a engineering documents, CAD files or configuring variants, work packages, typed attributed graph, which can be prototypes, can be supported and parts and service releases. Additionally it analysed by common patterns, such as incremental product innovations are is useful to plan sales and service release attributes, structures, dependencies, etc. facilitated. offerings as well as specific variant related A tool manufacturer used this intelligent service offers. A global premium automotive OEM uses method to identify redundant parts and a solution finder during the product With this tool a crane manufacturer to optimise the existing product development process to find and re-use implemented a modern, service oriented structure. The visualisation of the product 3D-constructions of similar constructions. sales process. Improved conversion rates, variant components in a “network- In this way, the company reduces shorter lead time and an additional self format” facilitated the compilation of a developing lead time and costs, minimises service configuration have been leveraged standardised toolbox reducing the amount redundant work and reaches a faster as benefits. This led to additional revenue of required components. Today the tool time-to-market. In addition, it is able to in the field of service offers, improved is used in daily business to assess the eliminate unique parts already at the product performance, minimised suitability and conformity of new products design stage leading to a higher degree maintenance costs and optimised and components for the existing product of standardisation. service deployment. range and decreased the redundancy level significantly.

13 5. Become world class with product analytics

Just a few companies have integrated data (manufacturing process data, be applied systematically. It can also big data and analytics in their information sensor data,…) or supplier data function as a decision tool for preparing and technology environment in order to (delivery times, prices,…). objective groundwork for decisions support product complexity management. concerning the product architecture Depending on the solution the analytics However, the exploding amount of infor- or platform. tool carries out a consolidation, validation mation generated through clients, products and cleansing of the collected information, Analytics can be applied across the whole and processes and the need for agility before generating analytical predictions value chain. To concretise the approach make it inevitable to consider the imple- like a demand analysis for instance. The within product complexity management, mentation of analytical tools. findings are visualised in interactive tables we would like to provide a selection of These tools collect their data input from and appealing charts, making it easy to potential use cases. different sources, such as company get insights, support decisions and records data (transaction data, CRM, deduct further actions in product com- inventory levels,...), web-based data plexity optimisation. With the help of (GPS, social media, smart phone such a solution, elimination, addition or apps,…), third party data (credit card modification of the whole product and history, demographic data,…), product service family including all attributes can

Figure 4: Data sources for Big Data Analytics

COMPANY WEB-BASED THIRD PARTY PRODUCT SUPPLIER RECORDS DATA DATA DATA DATA DATA S

E § Archives (customer § Smartphone apps § Commercial § Operational data § Inventory levels of correspondence, § GPS providers: consump- when product is in raw materials R C

U contracts), ﬁnancials § Click streams tion patterns, credit use (e.g. vehicle § Delivery times

O § Transaction data, § Google search terms history, competitor processors) § Order book S CRM (sales data, § Social media data, benchmarking § Manufacturing § Prices A

T service data, (Facebook, Twitter, data process data (errors, § Product catalogue A payment history) blogs) Open data: capacity, log data, Service delivery data D § § § Call center records demographics, assembly line data) § Inventory levels sociographics, § Sensor data economics (GDP), § GPS census § RFID tags

14 Next Generation Product Complexity Management Customer needs analysis and design

Figure 5: Customer needs analysis and design

Step in Value Chain

Requirements Design speci cation

Data Sources Key Drivers

1 2 3

Company Web-based 3rd Party Competition Customer Gobalisation records

One of the problems that organisations can be identified and offered for decision The benefit of this approach is the elimina- have to tackle on the customer side is that taking. The combination of internal tion of unnecessary differentiation resulting customer requirements are often fuzzy (e.g. historical CAD, CAE, PLM and CRM in fewer product variants (or more specific and unstructured or even just not known. data or social media data) and external variants) and hence, reduced complexity That can result in product offerings that information sources (e.g. sales data from in the sales, production and sourcing do not suit the market. It is also one reason sales platforms, search engine research process. In addition, it comes with some for product cannibalisation due to inac- or demographic trends data) serves as implementation barriers such as availability curate differentiation and increased input for a sentiment analysis or predictive and applicability of data, missing decision production costs due to unnecessary modelling to identify patterns that makes criteria or insufficient data series. But in work or missed use of equal tools. it easier to draw conclusions with direct order to use market insights for product affect on parts and model variants. For design decisions the customer need Thus, the challenge is to specify customer example, criteria-based rules for the analysis is a valid and intuitive tool to use needs concerning desired variants exactly design stage can be defined so that new analytics in this context. in accurate product offerings without features, such as e.g. colour or measures creating cannibalising products. With a can be automatically denied for new detailed customer needs analysis, profi- designs. table product variants or even features

15 Communal parts optimisation

Figure 6: Communal parts optimisation

Step in Value Chain

Requirements Design Product speci cation series concept

Data Sources Key Drivers

1 2 3

Company Product Competition Technology records

Another key challenge during the product structure- and pattern-based analysis. In to each other becomes more flexible, creation process is that many product this way, components for each product interactive and better maintainable. Thus, variants lead to high diversity of parts. variant are displayed in form of a network the visualisation serves as an intuitive Naturally there is nobody in the organi- and links between parts as well as decision support for an optimisation of sation who knows every product in redundancies can be visually identified. the existing product portfolio as well as detail and can find communal parts With filtering functions the views can an input for decisions concerning new systematically to identify those that are be tailored easily to certain topics and products and components. not needed anymore. Additionally, in use cases. most of the cases, the features are so The complexity management profits from complex that inter-dependencies and this visualisation of product variant compo- commonalities between the individual nents as a network facilitates the compi- components cannot be easily recognised. lation of a standardised toolbox while Visualising product components in a reducing the amount of required compo- network can help to remove parts redun- nents. Transparency concerning the dancies through the identification dependencies within the product portfolio of commonalities. seems to be the key to success. Thanks An analytical parts visualisation tool conso- to the communal parts visualisation, lidates the latest product component data companies are able to speed up the in one consistent attributed graph. processes of data collection, processing Repetitive tasks are formalised in rule sets and visualisation by substituting manual enabling the user to perform an attribute-, work. Linking different components

16 Next Generation Product Complexity Management Customer lifetime value optimisation

Figure 7: Customer lifetime value optimisation

Step in Value Chain

Sales

Data Sources Key Drivers

1 2 3

Company 3rd Party Customer Gobalisation records © Capgemini Consulting 2015

On the sales side it is obvious, that current costs), payment behaviour, shopping or the identification of parts that run the and future customers create more and frequency, external credit ratings are best and for making them available also more data as the digitalisation of the sales integrated in the calculation. for other products from other product channel is standard today. The challenge families or brands. For product complexity management this is, that customer groups are not easy to means that this measure can be used as The extent of the decision making impact segment and also relationships and a valuable input for decisions related to and value the information brings into the interdependencies of customer require- grouping and differentiation of products, decision process highly depends on the ments are hard to identify and capture. brands and local variants. Potentially input data available. If applied intelligently, Since some customer groups generate unprofitable product variants or features benefits of this use case are generated in significantly more revenues than others, can be identified, discussed and priori- the fields of cost optimisation in customer the evaluation of customer relationships tised accordingly. Key for this use case is service and offerings, increased customer is crucial. The measure “Customer the combination of data from outside and loyalty among most profitable customers Lifetime Value” is used to conduct inside the organisation. To get meaningful and higher customer satisfaction through customer segmentation and to manage insights the variables have to be selected supply and service optimisation. marketing-related measures. Present intelligently and combined based on one and future revenue streams and costs common goal, which can be for example (e.g. customer-specific advertising the elimination of unprofitable components

17 Production process complexity optimisation

Figure 8: Production process complexity optimisation

Step in Value Chain

Realisation / Assembly Service

Data Sources Key Drivers

1 2 3

Company Product Supplier Customer Gobalisation Technology records

Along with an increasing number of monitor machines and control operations. As a majority of costs is hidden in design variants comes a demand for increasing This allows ubiquitous process control errors that result in production inefficien- flexibility of the production sites in terms and optimisation to identify conspicuous cies this is a promising method to optimise of process agility. The vision to be able to defective parts and problematic or non- by a specific but beneficial lever. The produce every product in all production profitable product variants. Moreover, approach leads to products that are more sites in the world is not within reach actual site-specific production programme aligned with the given and future produc- under the circumstance of having an data across all product variants and tion capabilities. Moreover, it gives the increasing number of product variants. features can be generated in order to opportunity to detect product defects and But in order to enable standardisation of compare production variants to recognise can boost product quality, if fed back to the production programme data from the patterns. Those patterns can be used product development. site can be used and combined to give directly to optimise production variants, insights towards the product complexity. in order to minimise variety and complexity that comes along with each product With the digitalisation of the factory, real- category. time data from sensors becomes more accessible and can be collected to

18 Next Generation Product Complexity Management As good as all this sounds to a product Support infrastructure Solutions are quite individual and the manager’s ears, as equally important are Sufficient storage capacity to store ever business impact largely depends on the also the recommended parameters for increasing amounts of data has to be data situation available and used in this using product analytics methods for ensured and investments into databases context. But the possible benefits show product complexity management. and solutions planned early on. that becoming world class in product complexity management means to be High quality data Smart network capable of using the existing analytics As a foundation for further analytics, To ensure collaboration and sharing tools for the company’s competitive external and internal data that is used customer and product data the analytics advantage. has to be of good quality: consistent, solution has to be embedded into an error-free, available and relevant to be incentivised smart network of business integrated adequately. partners.

Analytics software All in all, big data analytics offers multiple The appropriate choice of analytics opportunities to provide insights in software should be tailored to business order to optimise product complexity. requirements and embedded in the strategic business context.

DATASOURCES PERFORMANCE COMPETITION OPTIMIZATION TECHNOLOGY ANSWERS LEADTIME OWNERSHIP

ARCHITECTURE SOCIAL INTELLIGENCE RESPONSIBILITY CUSTOMER VARIANTS CYBER-PHYSICAL BENEFITS MANAGEMENT SUPPORT PROCESS VISIBILITY REPORTING

TRANSFORMATION SCM TOOLS VALUE INDUSTRY4.0 DATA NETWORK DIGITIZATION OPERATIONS SCALABILITY PLANNING DECISIONS ANALYTICS COMPLEXITY ANALYSIS REQUIREMENTS VIRTUAL MANAGEMENT

CONFIGURATORSMART LIFETIME-VALUE WORLD-CLASS QUALITY INSIGHTS PRODUCTFAMILY MATURITY ENGINEERINGPLATFORMS GLOBAL COLLABORATION

STRATEGY COMMUNALITY

19 6. Start today!

Product architecture and platform locations is the key to dominate product jumping point to become world class. management is surrounded by exciting complexity. Sensors, machine to machine Where to start the journey truly depends developments, such as “Industry 4.0” or communication and data flows from on the organisational maturity in product the fact that globalisation has become clients through connected supply chains architecture and platform management. a reality. These trends and challenges, are only a few examples of information We identified five stages in which compa- however, bear an extreme potential for sources. The intelligent analysis and nies can be classified. product complexity management, if smart combination can provide valuable addressed properly. Moreover, lever- business insights and action proposals for aging the increasing amount of data reducing product complexity. Neverthe- over the whole value chain and across less, product analytics is really the

Figure 9: Journey to world-class product architecture and platform management

World-class product Architecture and platform management

INSIGHT-DRIVEN COMPLEXITY OPTIMISER

Optimises its product variants and portfolio on VALUE CHAIN BENEFITS SEEKER an insights-driven basis with business analytics methods seeks additional high benefits. Seeks value and benefits from anchoring consequent complexity management across ARCHITECTURE PROCESS OPERATOR every step of the value chain. Has consequently established processes and organisational governance behind product PRODUCT-PORTFOLIO PLATFORM APPLICANT architecture and platform management. Has identified the benefits of product communality management, applies product platforms PRODUCT MANAGER and optimises its product variants regularly. Knows about the complexity of its products and services and manages the portfolio ad-hoc or customer based.

Managing complex products

20 Next Generation Product Complexity Management In the first stage, the organisation knows The fourth stage represents the value 5. Develop and align the product about the complexity of its products and chain benefits seeker. Those companies architecture process services, but their ability to manage its manage complexity by anchoring 6. Define requirements towards tools and complexity is narrowed, we call them consequent complexity management systems product manager. They manage their across every step of the value chain and 7. Optimise product variants and product portfolio ad-hoc or customer- make decisions and impacts transparent configurations based, but are not able to plan upfront. An for each step. A crucial solution element 8. Operationalise variant and platform easy to implement tool those companies to get into that stage is an integrated SCM management use is a basic sales and service variant demand planning and forecasting with For a successful transformation of product configurator that serves as an interface to a clear link to product architecture and complexity management towards world the customer to show complex indivi- platform management. class, it is essential to engage people’s duality without shaping complete new The highest maturity in product architec- minds and hearts - this is what Capgemini requirements. ture and platform management is gained Consulting approaches with digitally In the second stage, the product-portfolio by companies that manage complexity as enabled change management. Proven platform applicant already has identified an insight-driven complexity optimiser. measures and new technologies are the benefits of product communality In doing so, they optimise their product combined in a change approach tailored management, applies product platforms variants and portfolio with business to the needs of our clients to balance the and optimises its product variants on a analytics methods and seek additional rational and emotional side of change regular basis. A common and proven benefits. Thus, becoming world class in and fully integrate change management solution element is a continuous and product architecture and platform activities in the transformation. rule-based product portfolio and variant management is strongly connected to the The integrated approach of product planning as a basis for quick reaction to digitalisation of the organisation and data architecture and platform management short term disruptions. structures surrounding it. by Capgemini Consulting offers multiple The architecture process operator in As stated before, it depends on the possibilities to professionalise your the third maturity stage has consequently company’s individual maturity, what range product complexity management. It is established processes and organisational of measures and tools should be used essential to assess the maturity of your governance behind product architecture for a transformation. Once the maturity is own capabilities to make deficits and and platform management. An integrated screened, the targets and priorities for the possibilities transparent. Additionally you product architecture process is used future product architecture and platform should think about solutions that best suit in parallel to the product development management are derived through an your products, services and customer process to bring stability in the complexity 8-step approach. environment and equip you for the of decision making along with a clear challenges of the future. So open up your 1. Analyse existing product portfolio and product architecture ownership with mind to the possibilities of “Industry 4.0” set architecture strategy dedicated responsibility. Decisions and start your journey now! 2. Structure existing product portfolio influencing the product architecture are 3. Analyse communalities across made on an objective basis using clear products KPIs and the qualitative knowledge from 4. Define architecture structure and former projects and key product manager. governance

21 Success factors for your journey to Next Generation Product Complexity Management: Product complexity management is a strategic topic and needs support · from top management, otherwise the measures are not sustainable and it leads to a one-off effect. Decisions around the product portfolio are not single decisions but have to · be controlled and steered professionally for all local markets globally. Mature data management is the basis for rational complexity decisions and · therefore extremely important. Product architecture and platform management is not only a technical topic, · but always has to involve the people and skills side to effectively steer decisions. To gain the benefits along the whole value chain, organisations need to have · high process maturity. Ownership and responsibility have to be defined and anchored to · guarantee that the decisions are made collaboratively and fact-based.

22 Next Generation Product Complexity Management 23 Contact:

Verena Gertz Felix Haeser Principal Consultant Senior Consultant +49 151 4025 1468 +49 151 4025 0998 [email protected] [email protected]

About Capgemini Consulting

Capgemini Consulting is the global strategy and transformation consulting organization of the Capgemini Group, specializing in advising and supporting enterprises in significant transformation, from innovative strategy to execution and with an unstinting focus on results. With the new digital economy creating significant disruptions and opportunities, our global team of over 3,600 talented individuals work with leading companies and governments to master Digital Transformation, drawing on our understanding of the digital economy and our leadership in business transformation and organizational change.

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About Capgemini With more than 145,000 people in over 40 countries, Capgemini is one of the world‘s foremost providers of consulting, technology and outsourcing services. The Group reported 2014 global revenues of EUR 10.573 billion. Together with its clients, Capgemini creates and delivers business and technology solutions that fit their needs and drive the results they want. A deeply multicultural organization, Capgemini has developed its own way of working, the Collaborative Business ExperienceTM, and draws on Rightshore®, its worldwide delivery model.

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