1. Helsinki University of Technology Systems Analysis Laboratory A Portfolio Model for the Allocation of Resources to Standardization Activities Antti Toppila, Ahti Salo and Juuso Liesiö Systems Analysis Laboratory Helsinki University of Technology P.O. Box 1100, 02015 TKK, Finland http://www.sal.tkk.fi firstname.lastname@tkk.fi

2. 2 Helsinki University of Technology Systems Analysis Laboratory Technical standardization n Agreement on a property of a good or service –E.g. railroad gauge, plug n Important part of R&D in the Telecommunication industry –Compatibility and interoperability –Access to a common pool of knowledge –Economies of scale n Our client was Nokia –Worlds largest mobile phone manufacturer (2007) »Spent more than EUR 5 billion into R&D

3. 3 Helsinki University of Technology Systems Analysis Laboratory Resource allocation into standardization n Challenges in standardization portfolio management –Value from standardization are difficult to assess –Hundreds of linked standardization activities to manage –Investments need to be aligned with company core competences –Contribution to market growth should be explicitly considered n Value capturing through widely adopted technologies –Widely adopted technologies yield more sales –Widely adopted technologies need development –Standardization contributes to the emergence of widely adopted technologies –Widely adopted technologies may emerge without standards through intensive technology development

4. 4 Helsinki University of Technology Systems Analysis Laboratory Standardization activity model Commit r S r D resources to an activity Standardization successful? 0 p s ( r s ) no Decision node Uncertainty node Value node 1- p s ( r s ) yes Sales Widely adopted technology successful? p d+ ( r D ) 1-p d+ ( r D ) yes no Sales p d- ( r D ) 1-p d- ( r D ) no No Sales r s = Standardization resources r d = Development resources p s = Standardization success probability p d+ = Development success probability (assuming standardization success) p d- = Development success probability (assuming standardization failure)

5. 5 Helsinki University of Technology Systems Analysis Laboratory Standardization activity portfolio n Activities managed concurrently –Shared budget constraints –Interactions among activities n Portfolio model –Uncertainties of activities modeled with decision trees –Decisions variables: resource allocation to the activities –Maximize portfolio expected sales n Discretized problem solved with Zero-One Linear Programming A B C X

6. 6 Helsinki University of Technology Systems Analysis Laboratory Elicitation of parameters n Current resource plan a point of departure n Estimates of success probabilities and prospective sales –Sales expressed as an interval, e.g. [50,100] M€ –Resource levels discretized »Standardization and (conditional) development success elicited for -100%, -50%, +0% and +100% changes to current level n Calculation of total success probability p tot = p s p d+ + (1 – p s ) p d- rsrs psps 1 0 rdrd 1 0 p d+ p d- Prob. of success p tot -100%-50% +0% +100% -100%-50% +0% +100%

7. 7 Helsinki University of Technology Systems Analysis Laboratory Efficiency of the current allocation n Optimal resource allocation significantly different from the current Budget Expected sales Maximum expected sales with current resources Minimum resource requirement for current expected sales Current resource allocation

8. 8 Helsinki University of Technology Systems Analysis Laboratory Activity-specific decision recommendations n Interval sales imply multiple optimal resource allocations n Core Index for each activity-specific combined resource allocation is defined as the share of optimal portfolios with this allocation (cf. RPM; Liesiö et al. 2007) –Black: All optimal portfolios contain the allocation –Gray: Some optimal portfolios contain the allocation –White: No optimal portfolios with the allocation n Provides reallocation recommendations Activity B Standardization resources -100%-50% +0%+100% -100% -50% +0% +100% Development resources -100% -50% +0% +100% Activity A rdrd rsrs

9. 9 Helsinki University of Technology Systems Analysis Laboratory Activity interactions n Challenging to model –Numerous interactions identified –Some of these difficult to quantify –No statistical model for reference n Systematic elicitation and qualitative visualization of interaction networks useful –Overview of linked activities –Clustering of closely related activities n Used a heuristic to model pairwise interactions Critical Competes Critical Beneficial Critical Beneficial Critical Competes

10. 10 Helsinki University of Technology Systems Analysis Laboratory Impact of heuristic interactions n Penalties/rewards for decreasing/increasing attractiveness of linked activities –Proportional to size of benefit, etc. n Decision recommendations with and without interactions –Holistic view of the impact –Reveals the interactions that affect the decision »Not always the strongest interactions –Enables revision of interactions -100%-50% +0%+100% -100% -50% +0% +100% Without interaction -100%-50% +0%+100% -100% -50% +0% +100% With interactions Critical A C Standardization resources of A Development resources of A

11. 11 Helsinki University of Technology Systems Analysis Laboratory Conclusions n Complex decision making problem –Intangible conceptual structure –Need for transparent parameter elicitation and analysis n Portfolio model for allocation of resources –Benefits of standards concretized through widely adopted technologies –Robust decision recommendations for resource adjustments n Unified management framework for standardization activities –Equitable treatment of all activities –Common terminology to discuss resource allocation into standardization

12. 12 Helsinki University of Technology Systems Analysis Laboratory References –Cooper, R., Edgett, E. and Kleinschmidt, E. (1997). Portfolio Management for New Product Development: Lessons Learned from the Leaders-I, Research Technology Management, vol. 40, pp. 16-19. –Liesiö, J., Mild, P. and Salo, A. (2007) Preference Programming for Robust Portfolio Modeling and Project Selection. European Journal of Operational Research, vol. 181, pp. 1488-1505. –Salo, A. and Liesiö, J. (2006). A Case Study in Participatory Priority-Setting for a Scandinavian Research Program. International Journal of Information Technology & Decision Making, vol. 5, pp. 65-88. –Sharpe, P. and Keelin, T. (1998). How SmithKline Beecham Makes Better Resource- Allocation Decisions. Harvard Business Review, March-April, pp. 45-57. –Shurmer, M. and Lea, G. (1995). Telecommunications Standardization and Intellectual Property Rights: A Fundamental Dilemma? Standard-View, vol. 3, pp. 50-59.

13. 13 Helsinki University of Technology Systems Analysis Laboratory Nokia n World’s largest mobile phone manufacturer (2007) –Global cell phone market share ~40% –Net sales EUR 51.1 billion (USD 80.2 billion) and operating profit EUR 8.0 billion (USD 12.6 billion) –More than 110 000 employees in more than 150 countries –R&D more than EUR 5 billion (7.8 billion) and 32% of workforce n Compatibility and Industry Collaboration unit (CIC) –Standards portfolio leadership –Industry relationships and collaboration –Regulatory compliance and leadership Helsinki University of Technology Nokia headquarters in Espoo, Finland ~1.5 km