Change Management: A Critical Component for Sustainable Enterprise Data Strategy

Nobody ever said data strategy is easy. Data strategy itself encompasses data governance, data management, and internal alignment with enterprise business goals. That doesn’t mean that there haven’t been many efforts to summarize ‘the top five steps to a data strategy’ or ‘data strategy made easy’. Even the latest AI-assisted software tools, although they help tremendously in terms of centralizing definitions, visualizing data lineage, and standardizing processes, don’t help with the ‘soft’ pieces of setting up a new data strategy program. By ‘soft pieces,’ I’m referring to the delicate balance of organizational structure and decision-making—in short, people and culture. 

What makes it so challenging to introduce a comprehensive data strategy isn’t the simple act of installing new tools or developing a roadmap. The problems arise in convincing stakeholders that changing methods or practices they have become familiar with—regardless of whether they are efficient or effective—is worth their investment in personal adaptation. Change introduces concerns, instability, and sometimes fear of giving up control. It can introduce concerns for the scope of individual responsibilities, or for the level of knowledge required to accomplish a goal. Or it could be ambiguity around how to modify existing relationships with colleagues and authority.  

“It must be considered that there is nothing more difficult to carry out, nor more doubtful of success, nor more dangerous to handle, than to initiate a new order of things.” (1)

In this era of rapid technical change, what follows is the need to adapt to new ways of doing business so we can realize the true value of data. We are challenged with making more data available to more and different kinds of users who support a myriad of types of business decisions. Indeed, managers must deal with new government regulations, technological developments, and a changing workforce. Some of these changes are genuinely exciting:   

• More accurate data 
• Faster access to data 
• Visibility into upstream and downstream processes and impacts 
• Freeing up data that has been hidden in silos within the organization 
• ‘Liberating’ data held in transactional applications   

These are just a few of the tremendously powerful capabilities that newer technologies have introduced.  

Yet on the counter-side are the potential ‘costs,’ which include fear of changing job expectations, a need for additional skillsets and retraining, new organizational relationships that potentially shift delicate balances of power, and locus of control. Peter F. Drucker has argued that the major obstacle to organizational growth is “managers’ inability to change their attitudes and behavior as rapidly as their organizations require. Even when managers intellectually understand the need for changes in the way they operate, they sometimes are emotionally unable to make the transition.” (2)

In some ways, it is surprising that human beings are resistant to change. Although we all strive for stability, most of us have acknowledged at various points in our lives the need to make personal changes—to become more mature, to acquire new skills, and to develop ourselves in ways that we believe will help us cope with the circumstances we find ourselves in.  

Organizations, too, naturally face the need to evolve to meet changing dynamics in the marketplace. Yet, even with incentives or mandates, enterprises typically encounter internal resistance. This resistance quite often results in a reactive, ‘fire-fighting’ mentality.  

One clear example that comes to mind are accreditation audits in hospitals and other healthcare facilities. Every three years, these enterprises KNOW they will be audited against carefully articulated standards on processes, documentation, and patient outcomes. And yet, every three years staff scrambles to produce evidence of compliance. One could claim that the accreditation audits don’t require committed staff more frequently, and that therefore it’s a waste of precious resources to continuously collect and monitor audit metrics. However, the result is that the organization does not take advantage of the defined metrics by continuously improving itself and developing its own capacity to more effectively respond during the audit period.  

Organizations can’t afford to overlook the need to rapidly meet constant challenges if they are to survive and compete in our ever-evolving marketplaces. And organizations truly need to anticipate change, as opposed to reacting to it. This needs to be a continuous process built into the enterprise.  

For this reason, Informatica has designed a Data Strategy Framework that includes an important underlying component of Change Management. 

Informatica Data Strategy Framework

Establishing a framework is critical to any data strategy program, because it provides the forum to set expectations and design ongoing communications materials that will break down pockets of resistance and provide feedback on program goals and accomplishments. 

A Strategy Requires Understanding 

In pulling together a strategy for change management, the organization will need to honestly and thoroughly assess their own internal culture. Informatica has worked on data strategy program development in companies as wide-ranging as the Department of Defense to small local companies. Regardless of the nature of the business, each organization needs to understand what methods will be effective and who needs to be involved. The rate and the pace of change needs to be tailored to the organization’s capacity to absorb new approaches.  

Strategic Continuum ⁽³⁾

Start with an evaluation of where on the following continuum best descrives your  organization’s culture. Collect the opinions of people from various business areas and discuss your findings together to understand where there are differing opinions and the underlying rationale. 

Take the opportunity to understand how the existing corporate culture drives an approach that the organization will be receptive towards. Understand the types of resistance you may encounter and think about ways to address these concerns.  

Diagnosing Reasons for Resistance 

• A desire not to lose something of value 
• A misunderstanding of the change and its implications 
• A belief that the change does not make sense for the organization 
• A low tolerance for change (fatigue) 

Managing Organizational Change—A Continuous Process 

Once an assessment has been completed and discussed with the decision-makers who will drive the data strategy, put together a change management plan to support the ongoing strategic initiatives. This plan should address the following components: 

Dealing with Resistance 

• Education and communication plan 
• Participation and involvement (set expectations for stakeholders) 
• Facilitation and support (clarify roles and responsibilities) 
• Negotiation and agreement  
• Manipulation and co-optation (where appropriate)  
  • Giving one of its leaders (or someone it respects) a key role in the design or implementation of a change 
• Explicit and implicit coercion (if it becomes a necessary option) 

The most common mistake managers make is to use only one approach or a limited set of approaches regardless of the situation. 

Use the following best practice to design a comprehensive approach: 

1. Conduct an organization analysis that identifies the current situation, problems, and the forces that are possible causes of those problems.  
2. Conduct an analysis of factors relevant to produce the needed change.
   • Focus on who, why and how much
   • Understand the relevant players and terms of power, trust and modes of interaction 
3. Select an appropriate change strategy 
4. Monitor the progress of the strategy and modify accordingly

Organizations may use this tool when planning and implementing a change management initiative. The steps outlined combine Kotter’s Eight-Step Change Management Model with Change Management considerations uncovered in secondary literature. (5,6,7,8)

Human beings (and organizations) are complicated, but they are adaptable. While it’s always helpful to have a framework and processes, templates and standard protocols, the fundamental challenge is how to change human behavior. And that touches on many more psychological components of how we as humans interact. Somehow, we need to find a way to demonstrate that a data strategy approach works for every individual involved. By doing so, it’s a win for everyone. 

Informatica Advisory Services can help develop the change management plan for your data strategy to ensure the full benefits are realized. We can help you map out the resources and timing to advance you toward the goals you need to succeed. And we can provide other real-life example of how similar clients have tackled their change management and data strategy challenges. 

References

1. Niccolò Machiavelli, The Prince. 
2. Peter F. Drucker, The Practice of Management (Harper and Row, 1954)
3. Diagram: See Larry E. Greiner, “Patterns of Organization Change,” HBR May–June 1967; and Larry E. Greiner and Louis B. Barnes, “Organization Change and Development,” in Organizational Change and Development, eds. Gene W. Dalton and Paul R. Lawrence (Irwin, 1970). 
4.  Kotter, JP & Schlesinger, LA; “Choosing Strategies for Change”, HBR July-August 2008
5. Guy Gregory and Karen Beaman, “Effecting Change in Business Enterprises” 
6. Accenture, “Uncompromising Leadership: Performance through Change”
7. Kotter, JP, “Winning at Change, Leader to Leader” 
8. Right Management Consultants, “Why Traditional Change Management Has Failed”