It's understandable to focus on the technology, use cases, and data when addressing digital transformation. However, to fully capture all of the value and be sustainable over the long run, an equal amount of focus must be placed on the processes, organization, and change management in order to ensure the long-term survivability of digital transformation initiatives.

Digitalizing or advancing the analytics and decision making in the organization enables a supply chain to mature beyond all-too-common scenarios of humans working through intensive, complex, and error prone Excel files. Conversely, this does not mean that entirely self-sufficient AI modules are put in place that enable end-to-end automation of the decision-making process. Rather, these data intensive initiatives require clear governance, subject matter expertise, and a comprehensive plan on how the organization plans to maximize the value potential.

• How can I leverage the resources historically responsible for this use case to maximize both their value to the organization and their satisfaction?
• Is the organization ready for this change, and if not, how best to communicate the future state and remove obstacles to acceptance?
• Who is going to ensure the inputs, constraints, and assumptions to the digital tool remain up-to-date?
• How will the outputs from the tool/application be socialized and implemented within the organization?
• Where will the team in charge of the tool/application reside organizationally?
• Do we have the expertise in house to take ownership of this capability?
• If we do not current have the expertise, how are we going to build it, or are we better off leveraging managed services?  

The number of use cases for digitalization within the supply chain increases daily. One of the major differences between those that succeed in moving away from Excel verses those that struggle is how ready the organization is to mature alongside the advancement of the tools at their disposal.