Risk Management, New Product Development, Business Intelligence, ... estimation of customer requirements, ignorance on global market situation and future ... AssessorTM software identifies 9 factors as determinant of product success.
NPD Risk Management: Proposed Implementation to Increase New Product Success Itziar Ricondo, Juan Antonio Arrieta, Nerea Aranguren IDEKO Technology Center, Arriaga Kalea 2, 20870 Elgoibar (Gipuzkoa), Spain {iricondo, jarrieta, naranguren}@ideko.es Abstract Innovation is one of the cornerstones of European manufacturing industry. For small and medium-sized (SMEs) enterprises NPD projects are very often a “win or lose” game. Due to the limited availability of resources, the risk of failure in a single project can endanger the survival of the whole company. SMEs have to deal with the following problems when undertaking the development of new products: (1) lack of information, (2) lack of a risk management methodology, and (3) lack of decision aiding tools. This paper recognises the need of acquiring suitable information and focuses on Risk Management as a critical process to increase the success of New Product Development. A staged implementation plan composed of 3 steps is proposed: Business Intelligence System, Risk Management System and Optimisation of Decision Making Process. Currently implemented systems and steps are commented, as well as future action points, in order to increase the competitiveness of companies. Keywords Risk Management, New Product Development, Business Intelligence, Project Management, Industrial Case
1
Introduction
Innovation is one of the cornerstones of European manufacturing industry. Large Companies increasingly use structured processes and tools to enhance the success of New Product Development (NPD) projects. However, for small and medium-sized enterprises NPD projects are very often a “win or lose” game [Klink et al., 2001]. Due to their limited availability of resources, the risk of failure in a single project can endanger the survival of the whole company. SMEs, indeed, have to deal with the following problems when undertaking the development of new products: •
Information Availability: Scarce information on concurrent technology solutions, false estimation of customer requirements, ignorance on global market situation and future perspectives, misleading interpretation of environmental or safety legislation and standardization procedures, are some of the issues to which SMEs have to face. An suitable information retrieval and capture system is required in order to provide SMEs with the most updated news related to the new technology tendencies, future market evolutions, customer needs, standardisation and legislation evolution. Porter and Miller [Porter, Miller, 1985] foresaw the significant effect of information technology on competitive advantage. Today, more than ever before, information technologies play a key role in the acquisition, storage and sharing of information and knowledge along the whole development process.
•
Risk Management: Risk management methodologies are not properly addressed in new product development processes. Furthermore, organisations have problems to manage risks and firefighting is a common practice in several organisations [Smith, Merrit, 2002].
•
Decision Making: Product development is becoming an increasingly complex process, involving a lot of strategic and operational decisions [Krishnan, Ulrich, 2001; Büyüközkan, Feyzioğlu, Orhan, 2002]: market, technology, customer, legislation, standardization, etc. Up to now the decision approaches followed by the SMEs have been based on intuitive decisions. Intuitive decision making approaches are no longer valid, due to the high complexity of the process design and development. Decision support techniques based on appropriate scientific approaches are needed to help small organizations making good decisions and to limit the risk involved in a new product development project. In order to solve these problems, three systems are required: 1. Business Intelligence System 2. Risk Management System 3. Optimisation of Decision Making Process These three systems can be seen and understood as a staged implementation process. The first step of the process is the implementation of a Business Intelligence System [Arrieta, Azkarate, Aranguren, 2004], oriented to the gathering of information for NPD decisions. Secondly, a NPD Risk Management system will provide organisations with a tool to better manage NPD projects. Risk Management will increase the success of new products, as well as the improvement of new product traceability, comparing product performance with risks maps. Finally, the management of risks implies making decisions, taking actions in order to decrease or remove the identified risks. For that purpose, organisation need to improve their decision making process, based on decision making techniques. However, the use of these techniques requires a culture change in some organisations. Therefore, the implementation of the Risk Management methodology will allow organisations to shift to a more proactive culture, in order to prepare them for the use of quantitative methods and techniques for decision-making. This paper is focused on NPD Risk Management. The most relevant works on risk management will be commented, which have been the basis for the definition of a NPD Risk Management System for non-serial product companies.
2
Risk Management approaches
Firms increasingly use formalized and New Product Development (NPD) structured processes, but have paid relatively little attention to the topic of risk management. However, the NPD success is around 55%-65% [Cooper, 1999]. Project Management Institute’s (PMI) PMBOK covers generic processes and practices, but it fails to address some of the technical, and many of the commercial and environmental issues that are crucial in determining the project success [Hartman, Ashrafi, 2004]. Designers often spend as little as 20 % of their time designing and for the remaining period they are searching for information. First of all, some definitions of risk will be provided. SEI defines risk as is the possibility of suffering loss. According to SEI definition, in a development project, the loss describes the impact to the project which could be in the form of diminished quality of the end product, increased costs, delayed completion, or failure. On the other hand, risk can be defined as the combination of the probability of an event and its consequences [PD ISO/IEC Guide 73] (it considers both positive and negative aspects of risk).
2.1
Risk identification
Authors offer several ways of categorizing product development risks (cf. Table 1). Smith and Merrit [Smith, Merrit, 2002] distinguish among six risk categories, whereas Klink et al. [Klink et al., 2001] use three major categories, technical, market and organisational risks, deployed down
in sub-categories. Keizer and Vos [Keizer, Vos, 2003] add the financial category. NPD-Risk AssessorTM software identifies 9 factors as determinant of product success. On the other hand, Keizer, Vos, Halman [Keizer, Vos, Halman, 2005] analyse ongoing NPD projects and identify, based on personal interviews, 142 risks, which they classified in 12 categories. This is the most extensive and detailed work in literature, where some new clusters to traditional risk management are identified: product family and brand positioning, commercial viability, product technology, manufacturing technology, supply chain and sourcing, trade customer acceptance, public acceptance, and screening and appraisal. [Keizer, Vos, 2003]
[Smith, Merrit,2002, p54]
1. Technology: product design and platform development, manufacturing technology and intellectual property.
1. Product definition 2. Development team 3. Quality and legal 4. Manufacturing. Outside resources 5. Technical
2. Market: consumer and trade acceptance, public acceptance and potential actions of competitors 3. Finance: commercial viability
6. Sales and Distribution
4. Organization: internal organization, project team, codevelopment with external parties and supply and distribution
NPD Risk AssessorTM, Adept Group
[Klink, Kohn, Paoletti, Levermann, 2001]
1. Product superiority/quality
1. Technical risk
2. Economic advantage to the user
−
Product concept development
3. Overall, company/project fit
−
Prototype development
4. Technological compatibility
−
Process ramp-up
5. Familiarity to the company
−
Fulfilment of regulations
6. Market need, growth & size
2. Market risk
7. Competitive situation
−
Competitors
8. Defined opportunity
−
Customers
9. Project definition
−
Substitute products
−
Suppliers
−
General market information
3. Organisational risk
1. Product Family & Brand positioning risks
−
Interface and communication
−
Idea acceptance
−
Insufficient resources
[Keizer, Vos, Halman, 2005] Risk Reference Framework 7. Trade customer risks
2. Product technology risks
8. Competitor risks
3. Manufacturing technology risks
9. Commercial viability risks
4. Intellectual property risks
10. Organization & Project management risks
5. Supply chain & Sourcing risks
11. External risks
6. Consumer acceptance & Marketing risks
12. Screening & Appraisal risks
Table 1: NPD risk categories attending to authors
To sum up, on an aggregate level it is clear that NPD risks categories should consider the technical, market, commercial and organisational aspects, deployed down in sub-categories and identifying factors within them for every project. However, these sub-categories and factors may be established for every industry, since a single set of project success factors may not be suitable for all industries [Hartman & Ashrafi, 2004]. There are several techniques to identify and elicit the risks, such as Assumption Analysis, Brainstorming, Checklisting, Delphi, Interviewing, Independent Assessment, Document Reviewing or Risk Database [Belliveau, Griffin, Somermeyer, 2002; Boyce, 1995]
2.2
Risk Management
Authors propose several methodologies for risk management, a process which has to be executed among a cross-functional team [Belliveau, Griffin, Somermeyer, 2002] in order to have a balanced view of the whole NPD process. On this matter, engineers may have the tendency to focus on technical aspects, since plenty of the development work will be carried out by technical staff [Smith, 2002]. However, it has to be pointed out that 90 percent of project risks are nontechnical. Smith and Merrit [Smith, Merrit, 2002] propose a 5 step methodology for Risk Management. Sarbacker and Ishii [Sarbacker, Ishii, 1997] present a three-stage model of innovative product development (Product envisioning, Product design and Product execution) and follow the same logic for their Risk Management methodology (Envisioning risk, Design risk and Execution risk), according to the stages of the development process. More detailed methodologies present a higher number of steps and include the organisational aspects of the risk management methodology, with activities such as the team establishment and learning actions [Belliveau, Griffin, Somermeyer, 2002; Keizer, Vos, 2003]. [Smith, Merrit,2002]
[Sarbacker, Ishii, 1997]
1. Identify
1. Envisioning risk
2. Analyze risks
2. Design risk
3. Priorityze and map risks
3. Execution risk
4. Resolve risks 5. Monitor risks [Belliveau, Griffin, Somermeyer, 2002] 1. Prepare
6. Prioritize risks and issues
2. Build communication with common language
7. Plan risk responses and manage issues
3. Generate a list of the team’s concerns 4. Classify
8. Integrate risk responses in program strategy and document project baseline commitments
5. Analyze the risk
9. Execute and control the risk 10. Learning from risk management activities [Keizer, Voss, 2003]
RISK IDENTIFICATION
RISK RESPONSE DEVELOPMENT AND CONTROL
1. Initial briefing between project manager and risk 7. Preparing of risk management session by project facilitator manager & risk 2. Kick-Off meeting: project manager & team and risk facilitator facilitator 8. Risk management session: project manager & team 3. Individual interviewing of participants by risk and risk facilitator facilitator 9. Drawing up & execution of risk management plan RISK ASSESSMENT 4. Development of risk questionnaire by risk facilitator 5. Answering of risk questionnaire by participants 6. Constructing of risk profile by risk facilitator
Table 2: NPD Risk Management methodologies
Risk analysis entails the quantification of risk events and impact. There are several analysis techniques, such as Decision Trees, Expected Monetary Value, Failure Mode and Effects Analysis, Montecarlo, PERT, Real Options Analysis, Scenario Analysis or Sensitivity Analysis [Belliveau, Griffin, Somermeyer, 2002]. However, the quantification of risks involves translating some subjective and qualitative issues through adequate scales [Smith, Merrit, 2002]. The
capability to assess properly the risks with the developed scales will be determinant to trust on others’ assessments and to be able to compare previous product risk assessments. Riek [Riek, 2001] lists the Lessons Learned about managing technical, commercial and NPD personnel risks. Some remarkable lessons are: •
Always analyse in the planning stage what commercialisation will require and its impact on the business.
•
Skipping development steps to increase speed to market is the road to disaster.
•
Management and project teams both need training in how projects are executed, good risk management and key project milestones.
•
Understand and track the use of competitive technologies.
•
Understand the manufacturing implications for any new product early in the development process.
•
Supply contracts for materials should be confirmed early in the validation stage.
• Multifunctional NPD teams require attention to team building. On the other hand, the biggest barriers to Risk Management are the lack of a cross-functional team and lack of proactivity, this is, a firefighting culture [Smith, Merrit, 2002].
3
Proposed Implementation in an industrial environment
As commented previously, the full implementation of a NPD Decision Making System is composed of 3 main stages, in order to increase the Product Development process effectiveness and, therefore, competitiveness of organisations: •
Business Intelligence System
•
Risk Management System
•
Optimisation of Decision Making Process RISK TAXONOMY
DASHBOARD Key metrics
4. TRACK & CONTROL MODULE 3. ACTION MAKING MODULE
1. RISK IDENTIFICATION MODULE 2. RISK EVALUATION MODULE
DECISION MAKING SUPPORT
EXTERNAL INFORMATION
DECISION MAKING TECHNIQUES
COMPETITIVE INTELLIGENCE
INTERNAL INFORMATION IS
Figure 1: Three main systems for NPD Decision Making System
First of all, the organisation should implement a Business Intelligence system to gather strategic information regarding the business. Once the organisation has adopted the Business Intelligence system, the framework to assess the product development process deployment should be established, by the definition of a Risk Management methodology. The Risk Management methodology identifies the critical factors affecting the success of the new product, providing a methodology to avoid or reduce the risks. The NPD process requires plenty of decision to be made. However, decision making in SME is often a rather intuitive process, with no assisting
tools. Managers make decisions based on their own judgement (based on available information and assessed against critical success factors), but don’t have techniques similar to the ones developed in other product development areas to support or simulate the consequences of their decisions. Taking into account that decision making is related to other organisational aspects such as organisational culture and empowerment, the optimisation of the decision making process is envisaged as the third and last step of the proposed implementation strategy. In the following paragraphs the first two implementation steps will be commented on.
3.1
Implementation of a Business Intelligence System for Information Availability
This section will explain the implementation of a Business Intelligence System (BIS) within a non-serial product manufacturing group. The developed BIS aims at gathering and analysing external and internal information in collaboration with customer companies. These customer companies work in the machine tool sector, but the methodology is open and customisable to other sectors. The main receivers or clients of the Business Intelligence System are the members of the Executive Team, which make the strategic decisions regarding the New Product Development: product, technology, target market, internationalisation, etc. Therefore, the dispersed and heterogeneous information and knowledge has to be identified, filtered, analysed and properly communicated, so they receive suitable information to make decisions. The following Business Intelligence Organisational Model (cf. Figure 2) has been established. The model is based on the close relationship among the BI Project Team (BI service provider) and the key Company Contact. Knowledge sharing is two-fold. On the one hand, different BI project teams may enrich from each others’ experiences. On the other hand, the information sharing among companies depend on the relationship among them. For example, the sharing of external information among a single industrial group is really valuable, in terms of shared knowledge and economical efficiency. Business Intelligence Organisational Model OTHER SECTORS COMPANY 1 UC KCC externo KCC UC 11
PM JP nn PT CL nn PM JP nn PT CL nn
...
KCC UC nn
...
...
COMPANY n
PM JP 55 PT CL 55 KCC UC 55
COMPANY 5
PM: Project Manager (BI service provider) PT: Project Team (BI service provider) KCC: Key Company Contact
PM JP 11 PT CL 11
COMPANY 2 KCC UC 22 PM JP 22 PT CL 22
Machine Tool Manufacturing Group
BI service provider PM JP 44 PT CL 44 KCC UC 44
COMPANY 4
PM JP 33 PT CL 33 KCC UC 33
COMPANY 3
Information flows Knowledge sharing
Figure 2: Business Intelligence Organisational Model: BI service provider ↔ Industrial company BIS is supported by a suitable ICT toolkit. These tools (meta-searchers, meta-crawlers, data
processing tools, web watchers, file repositories, specific-purpose developed software...) are especially useful for the identification, filtering and gathering of information. Although ICT tools are also used for analysis, the BI project team does a good job in this analysis stage, which is
considered one of the highest value-added activities of the service. The machine-tool know-how is wisely applied on this stage. On the other hand, special templates and procedures have been developed in order to communicate and present the information to the customer. This standardisation of the outcome makes easier to the customer to gather and understand the suitable data, establishing some regular information channels: the Business Intelligence Platform, periodic bulletins, periodic face-to-face meetings with customers, etc.
3.2
Implementation of the Risk Management Framework
The Risk Management Framework has begun to be implemented within the New Product Development Process. Instead of presenting the Risk Management methodology as a separate and independent tool, the Risk Management will be implemented as another activity of the NPD process, being consistent with its object and reducing change barriers. Although the Executive managers and development team are used to managing plenty of information and making decisions, up to now there has not been a systematic methodology for NPD Risk Management. A Risk Scoreboard (cf. Figure 3) has been developed, identifying 9 risk categories and several subcategories and subsequent factors. These factors are being revised and validated by Technical and Innovation managers within selected manufacturing companies. On the other hand, a simple risk probability and impact evaluation method has been established (with low-medium-high scales). This evaluation method has to be validated by NPD personnel. Anyway, it is critical that all the personnel involved in the NPD decision making learn to evaluate attending to established criteria, in order to reduce the variability of the measurement system. This will be one of the determinant factors for the NPD Risk Management methodology acceptance. Risk Scoreboard Market
25 Finance
20
Competitors
15 10 5
Organisational
Product
0
Commercial
Manufacturing
Technology
Intellectual Property
Figure 3: New Product Risk Scoreboard
The aim is to continually feedback the Risk Scoreboard (identifying new risks) and to create a NPD Risk Management Knowledge System, in which past NPD project could be consulted and project risk Radar profiles compared (project-project comparisons, etc).
4
Conclusions
This paper has studied the NPD Risk Management process, which has not been properly implemented in SMEs and can strongly influence the success of the new development products.
Anyway, a Risk Management methodology requires a suitable information system to be implemented, in order to gather strategic information regarding technology, competitors, market, etc. The developed and implemented Business Intelligence System has been explained, as well as the given steps in order to implement a systematic and structured Risk Management Methodology within the NPD process. The following implementation challenges have been identified: (1) validation and continual feedback of risk types, (2) planned implementation in order to reduce potential barriers, and (3) learning and tuning of risk evaluation method. References Arrieta, Juan Antonio; Azkarate, Ander; Aranguren, Nerea: Advanced Business Intelligence System Adapted to SMEs, Within a Defined Product Life-Cycle Management Frame. ICE Conference, 2004. Seville (Spain). Belliveau, Paul; Griffin, Abbie; Somermeyer, Stephen: The PDMA Toolbook for New Product Development, John Wiley & Sons, Inc., 2002 Boyce, T.: Commercial Risk Management; How to identify, mitigate and avoid the principal risks in any project, Thorogood Ltd, London, 1995. Büyüközkan, Gülçin; Feyzioğlu, Orhan: A decision-making approach for the new product development process under uncertainty. Twelfth International Working Seminar on Production Economics, 2002, February 18-22, Innsbruck (Germany). Cooper, Robert G.: The invisible success factors in product innovation, Journal of Product Innovation Management, Vol 16, No 2, 1999, p. 115-133. Halman, J. , Keizer, J.A., Song, X.M: Perceived risks in product innovation projects: development of a risk skeleton. 1999. Eindhoven Centre for Innovation Studies (Netherlands). Hartman, F; Ashrafi, R. Development of the SMARTTM Project Planning framework. International Journal of Project Management, Vol 22, No 6, 2004, p. 499- 510. Keizer, J.A. ; Vos, J.P.: Diagnosing risks in new product development. Eindhoven Centre for Innovation Studies. 2003. Keizer, J.A.; Vos, J.P.; Halman, J.: Risks in new product development: devising a reference tool. R&D Management, Vol. 35, No 3, 2005, p. 297-309. Klink, H.; Kohn, S.; Paoletti, F.; Levermann, A.: Co-operation between SME and research institutes reduces the risk of the innovation process. 7th EACI Conference Enschede, 2001, 9th-12th December, Netherlands. Krishnan, V.; Ulrich, Karl T.: Product development decisions: a review of the literature. Management Science, Vol. 47, No 1, 2001, p. 1-21. NPD-Risk AssessorTM. Adept Group. Available at: http://www.adept-plm.com/npd_riskassessor.htm. PD ISO/IEC Guide 73:2002 Risk management. Vocabulary. Guidelines for use in standards. Porter, Michael E.; Millar, Victor E.: How Information Gives You Competitive Advantage. Harvard Business Review, July 1985, p. 149-174. Sarbacker, Shawn; Ishii, Kosuke: A framework for evaluating risks in innovative product development. Proceedings of the ASME DETC`97: ASME Design Engineering Technical Conference. 1997, September 14th-17th. SEI: Continuous Risk Management Overview, http://www.sei.cmu.edu/risk/overview.html. Smith, P.G., Merritt, G.M: Proactive Risk Management: Controlling Uncertainty in Product Development, Productivity Press, 2002. Smith, Preston G.: Thirteen ways to mismanage development project risk: How to avoid those erroneous routes. Visions Magazine. July 2002.
