Please submit your answers via Canvas. Limit to max of six (6) pages. Include all references in
the footnotes.
Bear Corporation, a high-profile organization operating in the financial sector, uses data to
meet its most basic business objectives. At this time, Bear’s data is siloed and managed by
workers who had competing organization responsibilities and priorities. Consequently, Bear
struggles to perform routine work and became consumed by an ever-growing amount of data
generated by the organization.
Compounding matters, the organization struggles to keep pace with the global financial
marketplace. For example, Bear lacks standards to facilitate data interchange and
integration, and the organization struggles with lack of data consistency when advising senior
decision makers. Taken together, performing routine work at Bear became time-consuming,
expensive, and mixed in bureaucracy.
Further, Bear lacks the data management discipline that would allow the organization to
respond to changing economic conditions around the globe. For example, Bear has no formal
data governance, data architecture or data quality initiatives. Making it even more complex,
Bear, like most organizations, perform data management well at the workgroup level but see
no real need for improving its data practice, becoming data-centric or implementing a data
strategy at the enterprise level. Even though data was foundational to all its work, Bear does
not recognize and respect data as an asset, that is, something of value that needs to be
managed and controlled.
After some time and at considerable expense, however, Bear’s leadership was convinced it
needed a plan. It needed to set a compass bearing to help the organization prepare to be datadriven. Bear needs a data strategy to guide and improve:

• the quality of its data assets;
• the ability of its knowledge workers to use data assets productively; and
• its knowledge workers’ collective ability to use these data assets productively in support
of organizational strategy
Because the environment is rapidly changing, and knowing troubling times are ahead if the
organization does not be more proactive, corporate leaders have decided to make an
investment to develop and rollout a data strategy. Since Bear does not have the leadership and
expertise to drive this initiative, they have decided to engage an external consulting firm and
one of their data strategy consultants to deliver on the desired outcome.
As the data strategy consultant, how would you approach building a high-level plan and
enterprise data strategy for Bear? When development developing your strategy and plan, what
areas would you consider? What are the most critical things that must be done at the
beginning? Example and ideas could include, but not limited to:
• Leadership structure of the initiative (e.g., executive sponsorship, committees, etc.)
• Urgent messaging to appropriate audiences (think about change management and the
“A” of ADKAR)
• Change management plans
• Data vision, goals, objectives, supporting strategies, and key initiatives (identify three at
each level)
• Measures of success and key success factors
• Implementation roadmaps and plans? (e.g., processes, checkpoints, communications,
etc.)
• How could this be rolled out / planned in an agile way to achieve quick and repeated
wins?
• How would you ensure the data strategy aligns with the organizational strategy?
• How would you solicit information and feedback from stakeholders?
• What are likely blockers or inhibitors or success?
Good luck!!!