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DICE Framework - Explained

What is the DICE Framework?

Written by Jason Gordon

Updated at June 26th, 2021

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Table of Contents

What is the D.I.C.E Framework?How to Use the DICE FrameworkBreaking Down DICECalculating a DICE ScoreAcademic Research on D.I.C.E Framework

What is the D.I.C.E Framework?

DICE framework is a formulation to assess the likely success of a project based on objective measures. It is a widely accepted tool for tracking projects, managing portfolios of projects, and initiating two-way conversation at multiple levels of an organization.

Back to: OPERATIONS, LOGISTICS, & SUPPLY CHAIN MANAGEMENT

How to Use the DICE Framework

Partners (both present and past) at the Boston Consulting Groups Perry Keenan, Kathleen Conlon, and Alan Jackson first introduced the DICE framework. In 2005 it was first published in the Harvard Business Review, then it was republished Harvard Business Reviews OnPoint magazine. It was featured in HBR's "10 Must Reads on Change Management". In 2014 the tool got the patent. The DICE framework enables the organization leadership to manage the resources tactfully to achieve the best from a project. They can estimate the outcome during the process and can make the necessary changes accordingly. It also helps them to efficiently handle the issues before that have a completely devastating effect on the project.

Breaking Down DICE

In DICE, the D stands for the duration of the project, it can be the total duration of a project or the duration between two milestones of a project. The I stands for the integrity of the team with special emphasis on the team lead. Here the C stands for the commitment to change, it comprises of C1 and C2. The C1 is the commitment of the sponsors and senior executives and C2 is the commitment of those who are impacted by the change. E is the additional effort required of the staff members. Organizations can bring in successful changes from ideation to impact by assessing the projects against these four components.

Calculating a DICE Score

The formula for calculating DICE score is DICE= D+2I+2C1+C2+E Numerical values are assigned to each one of these to express them statistically. Duration < 2 months = 1 2-4 months = 2 4-8 months = 3 > 8 months = 4 Integrity Very good = 1 Good = 2 Average = 3 Poor = 4 C1- Commitment of the sponsors and senior executives Clearly and strongly communicate the need = 1 Seem to want success = 2 Neutral = 3 Reluctant = 4 C2- Commitment of those who are impacted Eager = 1 Willing = 2 Reluctant = 3 Strongly Reluctant = 4 Effort < 10% additional = 1 10-20% additional = 2 20-40% additional = 3 > 40 % additional = 4 Dice score falls into three zones, win, worry and woe. A score between 7 and 14 is win zone, that indicates a high probability of success. A score between 14 and 17 belongs to worry zone, it indicates that the success is hard to predict. Scores higher than 17 says the success is unlikely to be achieved, it is the woe zone.

Academic Research on D.I.C.E Framework

  • The hard side ofchange management, Sirkin, H. L., Keenan, P., & Jackson, A. (2005). Harvard business review,83(10), 108. This paper explores the DICE framework as a simple formula for calculating how well a company is implementing, or will be able to implement, its change initiatives. In this paper, the authors uses these four factors to predict the outcomes and guide the execution of more than 1,000 change management programs worldwide. Not only has the correlation held, but no other factors (or combination of factors) have predicted outcomes as successfully. 
  • Cracking the code ofchange, Beer, M., & Nohria, N. (2000). HBRs 10 must reads on change,78(3), 133-141. Today's fast-paced economy demands that businesses change or die. But few companies manage corporate transformations as well as they would like. The brutal fact is that about 70% of all change initiatives fail. In this article, authors describe two archetypes--or theories--of corporate transformation that may help executives crack the code of change.
  • Customer relationshipmanagement: An analysisframeworkand implementation strategies, Ling, R., & Yen, D. C. (2001). Journal of computer information systems,41(3), 82-97. This paper explores the concept of Customer relationship management in business. 
  • A transactionmanagement frameworkfor collaborative engineering, Sriram, D., Ahmed, S., & Logcher, R. (1992). Engineering with Computers,8(4), 213-232. This paper discusses the various novel functionalities of a transaction management system for collaborative engineering applications. It also establishes protocols for data consistency maintenance on the basis of application semantics and encapsulation of nonserializable data sharing in local databases rather than by the notion of global database consistency. Finally, it presents strategies for implementing these features using a commercial object oriented database management system (OODBMS) environment (ONTOS). 
  • SHARED-DRIMS: SHARED design recommendation-intentmanagementsystem, Pena-Mora, F., Sriram, D., & Logcher, R. (1993, April). In[1993] Proceedings Second Workshop on Enabling Technologies-Infrastructure for Collaborative Enterprises(pp. 213-221). IEEE. This paper suggests that a fundamental issue in developing collaborative engineering systems is the representation and management of the design rationale. In this paper, the authors describe an information system, SHARED-DRIMS, which was developed for encoding design rationale in DICE, a distributed and integrated environment for computer-aided engineering. 
  • A datamanagementmodel for designchangecontrol, Krishnamurthy, K., & Law, K. H. (1995). Concurrent Engineering,3(4), 329-343. This paper presents a data management model to support collaborative design environments. Specifically, the proposed model describes a multidisciplinary project in terms of the independent evolution of designs from the participating disciplines. Projects are coordinated through asyn chronous communication of design changes This paper discusses two salient features of the given model. 
  • Innovation andchange managementin small and medium-sized manufacturing companies, Susman, G., Jansen, K., Michael, J., Bukowski, S., & Stites, J. (2006). Final Report of Task,4.
  • Challenges in choosing an effectivechange managementapproach, Hudescu, L., & Ilies, L. (2011). Managerial Challenges of the Contemporary Society. Proceedings, 125.
  • Models ofchange management: A reanalysis, Mathews, J. (2009). IUP Journal of Business Strategy,6(2), 7. 
  • Deriving value fromchange management, Metre, C. (2009). Master of Science in Organizational Dynamics Theses, 28. This paper provides a theoretical analysis on the perception of change management initiatives, with a focus on how one can one optimize and derive increased value from change management efforts. The context of this paper is to determine the degree to which change management initiatives are successful. The paper intends to explore and catalogue reasons that control and predict change management success, and provide best practices identified from the scholarly literature.  
  •  DICE: aframeworkfor intelligent real-time control, Krijgsman, A. J., Jager, R., Verbruggen, H. B., & Bruijn, P. M. (1991). IFAC Proceedings Volumes,24(10), 13-18. This article presents the development of a real-time intelligent control environment: DICE. Main emphasis is given to the requirements of knowledge-based systems to be realized in a real-time system. This results in a multi-task environment with several expert system kernels running in parallel. A blackboard mechanism is used for intertask communication. A kernel of the system uses demons to control other expert system kernels. The article ends with some conclusions about the use of DICE as a framework for intelligent control.
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