Does Digital Transformation need to involve everyone? Change is hard, and sometimes it is very tempting to leave the laggards behind.
If we can’t change the people, we change the people! – Anonymous CIO in conversation with Jen StirrupIs this the right approach to #Digital Transformation? What’re your thoughts? Read more by @jenstirrupTweet
If we can’t change the people, do we change the people?
All organizations have data in common. Digital transformation is an integral part of business intelligence, which includes technical components such as data migration and management. Digital Transformation is more than creating an efficient approach to implementing advanced analytics; it also provides organizations with the prospect of new and enhanced products and processes.
One of the enablers in successful transformation is incorporating creative thinking through promoting an agile mindset within the workforce to support new levels of creativity and productivity.
Getting rid of people isn’t a very creative way of implementing digital transformation.
Who should be part of the team?
Teamwork makes the data transformation a reality. Imagine if you have a soccer team with just one great player. The team can’t depend on a single player to triumph the season. The same situation occurs for organisations. Like any sports team, even if you have a great executive, every department and individual needs to show effort for the company to succeed.
Who leads the team?
There needs to be an executive sponsor to drive the change. If there is no executive sponsorship, then the team members will misdirect their efforts, and there will be little or no guarantee of success.
McKinsey’s survey showed that without a clear vision and outcomes-based metrics to guide executives’ strategies and decisions, data transformation projects could drag on for years.
It needs to involve the business and the tech teams; nobody should be left behind. The objective is twofold; data is crucial as it connects organizations with their goals and serves as a compass to assist individuals, teams, and corporations to reach those goals. Then the data needs to be accurate and consistent, which requires teamwork. Data scientists need to work together with every member to seamlessly create a single source of truth for the organization.
Who needs to initiate the Digital Transformation discussions?
Ideally, the executive sponsor should initiate discussions. When reviewing an organization with Executive sponsorship and oversight, it becomes clear that the data issues are often horizontal across the organization.
Different departments can mean siloed data, which, in turn, means siloed insights — this reality results in pervasive problems well outside the silos. The departmental data silos are seemingly the biggest hurdle for companies aiming to harness the power of data.
Overcoming Insights Silos
Not just this, “insight silos” can be due to many factors, such as the lack of business expertise to understand the data well, or perhaps a bureaucratic inefficiency which means that team members cannot share the data among different departments. For active data transformation, organizations need to identify data analysts’ teams from all the departments of the company and find ways to get the teams to collaborate.
What should the Digital Transformation Team Process involve?
The data transformation process should be outcome-oriented. Progress can be made through collaborative safe to fail experiments. The team can set a challenging bar of success level that team members can reach, but they should have to expend energy and effort to attain. One best practice is to use the agile methodology to set small, iterative steps to success rather than conduct a marquee project which has a higher likelihood of failure. In this way, the executive sponsor can set up successful outcomes. Team members are supported since the possibility of scope creep should be identified and trapped earlier.
Agile is a time-honoured approach used as a collaborative approach involving cross-functional teams to design and build viable solutions and features robustly, test the outcome and enhance them in swift iterations. Agile data likewise relies on the joint strategy to develop and deliver where diverse teams including members of the business and IT operate in “data labs”, focused on generating reliable insights and address business priorities to realize productive data transformation.
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