'Closing the loops' – A case study of NPI decision making improvement



By Eliezer Shalev

NICE Systems



Implementing NPI performance improvements deriving from lessons learned within a risk mitigation plan in a dynamic business environment is a complex organizational change. A practical model for NPI improvements is presented through a case study of a redesign of NPI decision making process by introducing Gate Reviews for NPI phases. The gate reviews process is utilized to serve as a debiasing mechanism for cognitive biases that interfere with rational decision making. In the NPI program management level decision making critical control points, decision criteria and decision structure are expected to improve goal setting and monitoring. In the projects management level, proximal, concrete and predefined goals are expected to improve feasibility and exhaustiveness of plans. The model’s expected effectiveness is uniquely discussed by integrating insights gained from Cognitive Psychology and Project Risk Management literature, thus allowing for mitigation of “decision making risks” posed by cognitive biases.


New Product Introduction (NPI) programs scale and scope holds a considerable challenge for program management and for an effective planning and control. NPI programs consist of company wide projects, demanding synchronization of global organizational units, along a dynamic environment, market and technological uncertainty. The eventual success of NPI programs is measured by timely introduction of a reliable product, as well as readiness for production, service and marketing.

Risk Management is a crucial requisite for improving project planning and eventual success [13]. Current success rates show poor performance of NPI programs in overcoming basic risks for success [8]. Project Management literature emphasizes the current problems with risk management tools within the project management environment, and shows the high impact of project planning on project success [15]. Hence, improving the project plan may be an effective tool in order to deal with high-risk projects. This approach, of improvement of all planning processes may replace the traditional approach which focuses only on the improvement of risk management processes [15]. In addition, an effective NPI risk management plan for any organization should be customized according to major issues deriving from lessons learned from previously managed  programs, thus “closing loops” of process improvements.

In order to improve overall performance in NPI programs, an integrative approach should be taken for improvement of “Critical Process Success Factors” [14] in program level as well as in projects level. Program level critical process success factor is embodied in setting goals and monitoring their execution within an overall managerial attention. Goal setting, planning and control are embedded within top management decisions along NPI program phases. Thus, a practical model of improving NPI program level processes may be achieved by addressing managerial decision making over issues of schedules, content and readiness of NPI programs. This view allows translating NPI improvement initiatives into improved decision making processes as actual foci for improvement.

Decision making in NPI programs is subjected to cognitive biases [10] that defy normative rules of rational decisions [5]. Risk Management models and best practices (PMBOK, CMMI) tend to focus on descriptive process engineering aspects of mitigating risks, disregarding accumulating research on models of cognitive biases within project decision making [7]. To date, no attempt was made to implement decision making improvements in NPI programs, in view of decision making risks posed by cognitive biases. On the other hand, program management best practices such as “Gate Reviews” (“Phase reviews”; “Checkpoints”) can retrospectively hold substantial prescriptive value for debiasing NPI decision making. Combining insights from debiasing mechanisms of cognitive biases within a customized “gate review” process should therefore benefit NPI program management plan and control.

A critical aspect of NPI decision making is the ability to discern problems and disengage from a failing course of action. These decisions are prone to a cognitive bias known in the literature as “escalation of commitment” [6]. This phenomena is typically described as “sunk cost” or “entrapment”. Simply put, Time To Market decision to launch a product, while disregarding quality and readiness issues, is a typical NPI dilemma susceptible of a disengagement bias from a potentially failing course of action. This is a basic NPI decision making risk in the program level. Mitigation of such a decision making risk can be achieved through debiasing the cognitive aspects that might interfere with rational decision making. This debiasing effect can be accomplished by adopting a gate reviews mechanism that includes definition of critical decision making control points along NPI program, introducing predefined decision criteria for each decision making control point, as well as structuring the decision making process. The hypothesized debiasing mechanism for NPI decision making is based on the fact that decisions relating to program success or failure will be considered in sequential phases of the NPI program (along predefined “gates”). The decision makers will be required to consider the overall goal of readiness through proximal, concrete and predefined goals of readiness in every phase of the program, and thus is expected to diminish escalation of commitment [9].

Project level critical process success factor lies is in planning and according execution. The basic decision making risks for planning are feasibility and exhaustiveness. Plans might turn out to be unfeasible. Plans may also be poorly devised when critical activities are overlooked, under-scoped or under-resourced. A well known cognitive bias of planning is known as the “Planning Fallacy” [1] [3]. This bias can be accounted by a distal view of targeted goals leading to ill-defined activities, or over optimistic estimations. A complementary effect of planning, called “resource slack”, can be seen as a resource “buffering” effects of uncertain estimations. Such estimates might lead to exaggerated plans that are eventually consumed by an inefficient execution [12]. This effect can be seen as resulting from over-pessimistic estimations.

Planning towards concrete, proximal and predefined criteria poses an elementary “best practice” for improvement of control over NPI readiness. From a cognitive psychology perspective, debiasing planning fallacies (optimistic or pessimistic) may be explained by proximal and concrete definition of goals that reduces the psychological distance of goals, allowing for better planning of near future events [2] [11] as well as positively influence on their subsequent implementation [4].

A practical model for NPI improvements is presented through a case study of a redesign of NPI decision making process by introducing Gate Reviews for NPI phases. 



An extensive lesson learning conducted with NPI program stake holders raised issues of product content stability, on time delivery, sales and service readiness. Root cause analysis further revealed improvement opportunities for planning and control in program and project levels.

An initiative to improve those issues was implemented as a mitigation plan for upcoming NPI programs in two divisions. In the program level, concrete goal setting, covering all NPI program stake holders, as well as a structured control over readiness was introduced in program phases. In the project level, improved planning was accomplished by pre-defining specific and proximal criteria. Consequently, the mitigation plan encompassed a top-down redesign of the entire NPI decision making process and an implementation of an action plan for project planning gaps. The NPI decision making redesign was launched through a “Gate Review” methodology (see figure 1):

  • Managerial decision making control points were defined as “gates” along NPI life cycle.
  • Decision making criteria were defined as “gate review items” and “entry/exit criteria”. Gate review items included all relevant deliverables from various units.
  • Structured decision-making was obtained by a “sign off” procedure with gate review “owners” and “sponsors”.

The action plan to implement gate reviews process improvements consisted of an alignment of project plans towards the concrete and proximal goals embodied in the gate criteria. The action plan was carried out within management teams in organizational units participating in the NPI projects – Product Management, R&D, Operations, Services, and Marketing. The gate review roll-out was separately executed in two NPI programs. The change management methodology included the following elements:

  • Gate Review Process design by Corporate Quality.
  • Process communication and management buy in through gate review “Sponsors forum”.
  • Gate items preparations – follow up on action plan, as well as facilitating preparation of critical planning deliverables with program and project managers (gate review “owners”).
  • Gate reviews dry runs & sessions with predefined agenda and participants.
  • Gate reviews conclusions and immediate lesson learning for subsequent gates and similar gates in other divisions.

Fig. 1: NPI Gate Reviews

Fig. 1: NPI Gate Reviews


The gate review process is still under implementation and its effectiveness will be assessed through a follow up study of the actual improvement of product content stability, on time delivery and service and marketing readiness.



This case study presents a top down design of managerial decision making in NPI programs. It demonstrates how gate review mechanism may serve as a debiasing mechanism through deploying structured decision making process that includes definition of decision control points and decision criteria in the program level. Moreover, the gate review mechanism can be utilized towards improved feasibility and exhaustiveness of project plans, due to more concrete and proximal goals.

The following insights to the practice of R&D Risk Management are gained: First, basic model for improving NPI programs can be simply accomplished by better planning. Second, implementing lessons learned in risk mitigation in NPI programs illustrates the challenges of effectively “closing loops” of corrective action by channeling a past event into a future activity in program and projects level. This is a simple mechanism that often requires complex change management. Last but not least, this case study presents a risk mitigation plan aiming at decision making risk sources. The domain of risk management has thus far neglected research of decision making risks, embodied in cognitive biases of decision making. Drawing insights from decision making literature holds a vast potential for R&D Risk management improvements.

Future research should be conducted to empirically validate the practical benefits of debiasing decision making risks, as suggested in this case study. An example can be taken from a current study conducted by Shalev [9] that examines the expected effects of Risk Construal on Risk Recognition, Risk Mitigation and Disengagement from a failing course of action.


  1. Buehler, R., Griffin D., Ross M., Exploring the ‘Planning Fallacy’:Why People Underestimate Their Task Completion Times, Journal of Personality and Social Psychology, 67 (3), pp. 366–81, 1994
  2. Fishbach, A., Zhang, Y., Dhar, R., When Thinking Beats Doing: The Role of Optimistic Expectations in Goal-Based Choice, Journal of Consumer Research, 34, pp. 567-578 , 2007.
  3. Griffin, D., & Buehler, R., Frequency, probability, and prediction: Easy solutions to cognitive illusions? Cognitive Psychology, 38, pp. 48–78, 1999.
  4. Henderson M. D., Gollwitzer P. M., Oettingen G., Implementation Intentions and Disengagement from a Failing Course of Action, Journal of Behavioral Decision Making, 20, pp. 81–102, 2007.
  5. Kahneman, D., Lovallo, D., Timid choices and bold forecasts: a cognitive perspective on risk taking. Management Science 39, pp. 17–31, 1993.
  6. Keil M., Depledge G. & Rai A., Escalation: The Role of Problem Recognition and Cognitive Bias. Decision Sciences, 38(3), 391-421, 2007.
  7. McCray E., Purvis R.L., McCray C. G., Project management under uncertainty: The impact of heuristics and biases, Project Management Journal, 33 (1), pp. 49-57, 2002.
  8. Raz, Z., Shenhar, A.J., Dvir, D., Risk management, project success and technological uncertainty, R&D Management 32 (2), pp. 101–109, 2002.
  9. Shalev, Eliezer, Risk Construal in Project Decision Making – aim high or aim low? In press.
  10. Tiwana A., Wang J., Keil M., Ahluwalia P., The Bounded Rationality Bias in Managerial Valuation of Real Options: Theory and Evidence from IT Projects. Decision Sciences 38 (1), pp. 157–181, 2007.
  11. Trope, Y., & Liberman, N., Temporal construal. Psychological Review, 110, pp. 403-421, 2003.
  12. Zauberman, G., Lynch J. G., Resource Slack and Propensity to Discount Delayed Investments of Time Versus Money, Journal of Experimental Psychology: General, 134 (1), pp. 23–37, 2005.
  13. Zwikael, O., Globerson, S., Evaluating the quality of project planning: a model and field results. International Journal of Production Research 42 (8), pp. 1545–1556, 2004.
  14. Zwikael, O., Globerson, S., From Critical Success Factors to Critical Success Processes. International Journal of Production Research, 44 (17), pp. 3433–3449, 2006.
  15. Zwikael, O., Sadeh A., Planning effort as an effective risk management tool, Journal of Operations Management, 25, pp. 755–767, 2007


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