Unless it pertains to politics or parking meters, people dislike change. Why? Change involves work, learning new skills, and the possibility of failure. This makes people uncomfortable and resistant. Maintaining the status quo is simply easier. When we look at why BI & Analytics initiatives fail, the reasons are not usually technical problems, but people problems related to change management and communication. Yet, in contrast to the average stakeholder, individuals who lead change are enthusiastic advocates and willing to put in the extra effort.
Why is this?
Champions of change understand the “Why, What, and How” of the change that is taking place.
Most stakeholders do not understand the “Why, What, and How” This is where D&A strategies are failing. If you map these 3 critical pieces of information to hot trends in Data & Analytics it is very clear. Industry challenges include:
- Understanding the potential value of data – Rise of CDO (Data Culture)
- Developing the skills to use data – less than 24% (Data Literacy)
- Using BI to make decisions – less than 35% (BI Adoption)
- Producing a positive business outcome – less than 20% (Value)
Why, What, and How…
The “Why” must be the basis for change, and if it does not bring significant value to stakeholders, the initiative is doomed from the start.
All three of these factors are important, but the first is the most critical. To determine value, there must be strong communication between the analytics team implementing technology and the stakeholders who will use it. This is when we need to determine:
- What are the business goals or outcomes?
- What decisions will be made to reach these outcomes?
- What information is needed to make decisions and act?
This channel of communication between “Analytics” and “The Business” has been historically very weak. One reason that “change management” and “communication” are the most poorly executed components of an Enterprise Data Strategy, is because Data & Analytics initiatives are championed by technologists. While data scientists might be some of the smartest in the room, technology is their passion, not people. So, technology is what they focus on and the people side of analytics gets neglected. This has led to the rise of “Analytics Translators” and other intermediaries.
The titles for this role are wide-ranging and have little consistency, but the need for an individual to lead the change management aspect of D&A initiatives is apparent. Call this person an “Analytics Translator”, a “Data Champion”, a consultant…whatever gets the job done effectively.
This is the hard part. Every company has unique needs, strengths, and weaknesses. There are a number of things to consider when improving the change management aspect of your Enterprise Data Strategy or Digital Transformation effort in addition to a focus on the above:
- Do you have a clear leader and advocate for D&A on the executive team? Hiring a CDO is now a must.
- How does your analytics team work together and communicate with the rest of the business? Does your company have a dedicated analytics team or a (CoE) Center of Excellence? Should your company have a centralized or decentralized analytics team?
- Do you have dedicated individuals responsible for developing Data Culture, Data Literacy, and driving adoption? This is a full-time job. Hire for it.
- Is there a focus on business outcomes first and technology second?
We believe establishing an Enterprise Analytics Hub helps solve many of the challenges related to Data & Analytics change management. By centralizing all BI content in a single location and user-experience, you establish a foundation from which to build a data culture, communicate with end-users and receive feedback on business needs. You can also launch embedded data literacy campaigns and increase BI adoption by providing a single point of entry, and insulate end-users from the disruption that comes with the introduction of new tools and sunsetting of legacy systems.