Data & AI Strategy
A strong data strategy ensures that your data works for you, aligning with your business goals and making the most of your investments in technology and people.
Without one you risk wasting money and time producing expensive solutions that fail to drive measurable business impact.
Over the past 10 years AI and especially machine learning has become a essential part of most data strategies in order to maximise value from data.
More recently generative AI has made AI use a necessity to remain competitive, as it has enabled AI solutions with clear ROI to penetrate every industry and business domain.
What is a Data Strategy?
A data strategy is a comprehensive plan that outlines how an organization collects, manages, and utilizes its data to achieve its business goals. A full data strategy typically covers:
A vision for data and AI, and how you will measure its impact.
The technology required to achieve that vision.
The people required to deliver the technology.
The data management and governance required to maintain high quality data.
Enablers of data use such as data culture and literacy.
Other considerations such as compliance, regulation, ethics and trust.
What are the typical challenges with data strategy?
Effort - Time is required from a range of senior staff to input into the strategy.
Expertise - How many organisations have experience in all areas the strategy needs to cover?
Time - A data strategy can take several months to complete, time not spent building solutions which create actual value.
Cost - Often delivered by third parties, data strategies can cost hundreds of thousands.
Practicality - Data Strategies are often difficult to deliver, being too generic and lacking customisation.
Useable output - Delivered as a long PowerPoint presentation or document, they are difficult to communicate, execute and change along with the market.
How do you do it better?
Focus on use cases
Identifying and defining use cases that deliver measurable business value means your strategy is customised to your business and based around a real business case.
Build a roadmap
Aligning the use cases to a roadmap which details when, how and who is required to deliver them is essential to a realistically achievable strategy and set of outcomes.
Make it “alive”
Your strategy needs to be living and interactive, not a static document. Its easy to achieve this when you have the right tools for the strategy itself, as well as for delivery management.
Obsidian Shift’s automated roadmap generator
A better approach with Obsidian Shift
A targeted, practical approach to Data & AI strategy, focusing on practical use cases and business value. Typical completion time is 2-3 weeks.
Data Maturity Assessment:
2 hour guided assessment identifying maturity levels across over 50 data and AI topics. Delivered with our Data Maturity Assessment tool.
Leadership Workshop:
A half day workshop to:
Establish the organisations goals with data
Identify potential data and AI use cases
IT Workshop:
A half day workshop to:
Understand enterprise architecture
Understand existing data and AI solutions
Roadmap & Report:
A data strategy report for presentation consolidating the output of the assessments and workshops, as well as the data strategy recommendations.
An interactive implementation roadmap with use cases, timelines and requirements for delivery. Provided by our roadmap tool.
Discuss your strategy with us
If you’re interested in a review of your current strategy or to create a new one, please fill out the form or send an email to:
contact@obsidianshift.com