Guest Column | December 17, 2018

An Introduction To Tools And Methodologies For Improving Change Management

By Peiyi Ko and Tom Schiavon

Change-Ahead

In a business world where keeping up with competitors means leveraging evolving technologies, increased complexity and continuous demands for change have become more common. Systems are rapidly becoming more sophisticated in function and the integrations they offer, so keeping your systems, processes, and training up to date is crucial to operational success.

But implementing changes requires the proper planning, execution, and flexibility. Studies indicate that 53 percent of organizational changes fail to keep to budget or timelines or do not fulfill the intended purpose, nearly half are partial failures, and some even have a much higher failure rate of 70 percent.1 For changes in software in the pharmaceutical space, any glitches or errors could have catastrophic repercussions, including affecting patient safety or causing significant program delays. Because the stakes are so high, thoroughly validating critical components isn’t just a good business practice, it’s an ethical decision.

In this two-part article, we will look at a change management model derived from the concept of co-creation, a process in which brands and consumers work together to create better ideas, products, and services. In this first part, we discuss the tools and methodologies that provide a foundation for improving change management. The second part will look at strategies for implementing an improved change management process.

Identifying The Primary Obstacles To Success

In their 2014 article Change Management through Learning Factories, Dinkelmann, Siegert, and Bauernhansl highlighted the four key challenges for change management:

  1. Employee resistance
  2. Lack of process control
  3. Speed at which change is implemented
  4. Unclear goals1

The pharmaceutical, life sciences, and medical device industries deal with the above, in addition to other obstacles.  The industry’s top concerns around ineffective change management include:

  1. 97 percent of survey respondents considered that post-approval changes to process hinder technology progress2
  2. Unintended consequences often occur when making a change3 
  3. Compliance concerns due to inconsistency or errors associated with lack of standard processes
  4. Manual maintenance of unstructured data and revisions

Co-Creation As A Solution To Change Management Failures

Research has shown that a top-down approach to change will encounter more resistance and introduces risk into the change management process. Also, morale suffers when employees realize their voice doesn’t count. To counter this, a bottom-up approach is proposed, involving as many people as possible in the process to minimize resistance. Although this model requires investing more time and resources, studies show resistance to change is lowered and the results are more sustainable.1

This model is in line with the concept of co-creation, which has been discussed for many years but popularized more recently as a business strategy focusing on joint creation of values by a company and its customers. Given the fast-evolving and collaborative nature of today’s market, it allows a company to leverage the experience of the customer, expanding the insights that can be gained to increase the value output of the project. In the context of change management, this philosophy can be extrapolated to how teams collaborate to make a change project successful.

Refining Co-Creation For Sustainable Results

To address these challenges, we suggest a methodical approach informed by classic and emerging trends in strategy and technologies and the insights of Cognitive Work Analysis (CWA). The process begins with a business system analysis to capture the applicable work practices, then using the information garnered to design business processes or tools that facilitate effective team collaboration and set the foundation for innovative continuous improvements. The model is built on three pillars: Analysis, Reprocessing, and Engagement.

Analysis

In the Analysis phase, a system analysis framework is used to capture business processes and work practices to highlight gaps and opportunities for improvements. Through interviews, meetings, site visits, online surveys, and key document reviews, a complete view of the project, program, or operations is created.

Reprocessing

By abstracting the sociotechnical landscape and dependencies, as well as identifying gaps in organizational structure, tools, processes, or learning, the model provides useful analysis as the foundation for success. The results may include the overall interactions between organizational departments and layers and includes cost analysis to ensure budgets are able to be allocated appropriately. The diagramming and understanding are an evolving process that often employs rounds of clarifying goals, identifying dependencies between process and organizational elements, and performing iterative organizational groupings for alignment within the business structure and goals.

Engagement

From the Reprocessing step, customized workshops and detailed training opportunities are planned to socialize the insights gathered to key stakeholders. The model emphasizes leveraging the knowledge and experience of all levels of employees to understand the “true structure of the organization” or “the reality on the ground.”  Establishing a holistic picture is the key to engaging employees proactively, anticipating resistance, and providing them with the tools and training to make the transition as seamless as possible. It may also be useful to discuss and introduce emerging technologies, such as tools for analytics, data workflow automation, customized apps, or interactive dashboards to ensure organizations build in scalability and agility.

These three elements establish the foundation for better planning, process improvement, tool utilization, and effective training to support change management.

Define Dependencies And Situations To Align Strategies And Operations

Using a Cognitive Work Analysis (CWA) approach allows the complex sociotechnical aspects to be mapped and included to make a more thorough analysis. By using a Work Domain Analysis (WDA) to identify abstract principles like purpose and values down to the physical functions and objects used to complete work, a more holistic understanding of the work environment is gained. Once understood, diagramming the framework creates a “consistently sensible” sub-analysis that serves as the basis for organizing relevant information surrounding the operations, program, or project. When combined with the proper analysis, the results deliver actionable information to make informed decisions.

One possible example would be a company looking to improve efficiency in the manufacturing process. The typical focus on updating its machinery, improving training, or streamlining processes is crucial, but hidden dependencies or unexpressed frustrations from front-line employees may derail the efforts if not fully understood. When the management team begins to make decisions among competing options, this lack of information can cause not only easily quantifiable losses, such as manufacturing downtime or reduced output, but also in areas that are less easy to measure, such as employee satisfaction and motivation. In an article on The Benefits & Challenges of Business Process Automation, Ayesha Khan cites the following benefits of automating processes:

  • Focusing less on small tasks to empower customer service
  • Integrating disparate systems
  • Dynamic task assignment

Although these benefits are attractive, the challenges must be balanced as well, which include:

  • The difficulty of integrating systems
  • Morale suffering due to fear of jobs lost through automation
  • Additional engagement to monitor the automation4

Two tools that are exceptionally useful for transforming data into interactive visualizations that provide actionable information are dependencies plots and situations plots.

Dependencies Plot

A dependencies plot is a visualization tool used to construct a holistic representation of system or program elements. It gives decision makers a top-to-bottom visual understanding of the processes while also helping members of an organization understand how their work contributes to organizational success and accomplishing project goals. As a result, both the decision-making and contribution framework are made synergistic.

Using an interactive dependencies plot,5 the viewer can highlight related dependencies and links by hovering over a square in the dependencies plot — representing a project element, tasks, or stage. The path can also be highlighted to identify gaps. At each level, the effort or percentage of resources required are noted as a percentage of the whole, so resource allocation is clearly illustrated. Each box can be flexibly assigned to one or more roles or teams, allowing the user to see cross-functional tasks and a rough project narrative. Customized tags may also be used to show regions, priorities, or any other set of classifications.

The visual also can be used as an effective communication tool, allowing the creator to embed information that makes the output more illustrative. When embedded hyperlinks are incorporated, reports, dashboards, and analytics stored elsewhere become part of the analysis, leveraging a large amount of data to make decisions. Resource numbers can be used to aggregate upward or be divided based on specified ratios downward, adapting to the evolving needs of a project for simplified decision making and metrics tracking.

Situations Plot

The situations plot further empowers leadership by providing high-level insights into the work practices under various situations and can be used to discuss implications of multiple “what if” scenarios. As any project is limited by time, resourcing, and cost constraints, it is crucial for management to have clear and actionable information when considering options. Having a structured framework to examine the decision-making process also expands workflow optics to avoid blind spots when introducing changes. The decision analysis aims to enable more effective knowledge generation and sharing by articulating how decisions are made, highlighting common work practices in different situations, and showing relations to each other across the organization.

In an interactive situations plot diagram,5 the overall project steps, resources, and dependencies can be programmed into the plot. By selecting customizable situations and scenarios from the drop-down menu, the viewer can see the process steps and consequences of a decision for a particular situation. The high-level decision-making archetype includes the main steps, substeps, options, and outcomes of each substep connected to other items. Hyperlinks can be inserted to the corresponding element to extend use and add context to the knowledge, whether for onboarding new resources or to capture lessons learned. By comparing different versions of the analyses (by adding interviewees, document reviews, observations, or scope of the analyses), changes can then be proposed and discussed.

In the second part of this article, we examine strategies for implementing changes using the co-creation model.

References:

  1. Dinkelmann M., Siegert J., Bauernhansl T. (2014) “Change Management through Learning Factories.” In: Zaeh M. (eds) Enabling Manufacturing Competitiveness and Economic Sustainability. Springer, Cham, pp 395-399.
  2. Ramnarine E. (2017) “Postā€approval Change and Knowledge Management – Where are We? Results from the PAC iAM Task Force.” PDA Annual Meeting 2017. https://www.pda.org/docs/default-source/website-document-library/workshops/2017/pac-iam/emma-ramnarine-pac-survey-results.pdf/
  3. Axendia Inc. (2016) “The Future of Change and Configuration Management in the Med-Tech Industry” (white paper). http://axendia.com/wp/are-you-a-med-tech-innovator-or-laggard/
  4. Khan A. (2017) “The Benefits & Challenges of Business Process Automation,.” TechBlocks. https://tblocks.com/blog/2017/08/02/benefits-challenges-business-process-automation/
  5. https://kocreationdesign.com (2018)

About The Authors:

Peiyi Ko, Ph.D., CHFP, founder and principal of KoCreation Design LLC, strives to help companies and teams set the foundation for innovative continuous improvements in operations and work environment. To create opportunities for positive changes, she applies human-system interaction research and human-centered design to develop a framework for decision analysis, training design, and project communication. She has guest lectured at universities and led workshops. Previously she provided human factors/ergonomics consulting as well as software usability analyses and design recommendations at BSI EHS Services and Solutions and the Lawrence Berkeley National Laboratory. You can reach her at info@kocreationdesign.com and visit www.kocreationdesign.com for more information on the methodologies and tools.

Tom Schiavon, M.A., is an experienced project manager who enjoys exploring the intersection of theory and practice to innovate or improve processes. He gained an understanding of supplies management while serving as an IRT project manager and manager of technical support and data management teams. He obtained his M.A. in English from Florida Gulf Coast University, where he also graduated summa cum laude as an undergraduate. A humanities wonk by nature, he enjoys contributing to the development of novel medications aimed at easing human suffering. As an associate consultant with KoCreation Design LLC, he helps tell the story of the company’s unique mission and approach.