Enterprise Data Strategy
February 27, 2020
Houston, TX, USA- Hosted by Chevron
Our ability to generate, collect and combine data, both internal and external, grows by leaps and bounds. To quote our colleague John Gallant’s 2018 pamphlet on the subject: “There’s never been so much data to work with; There have never been more users and consumers of data; There have never been more examples of data-driven disruption.” Whether it is being used to create new business model possibilities for enterprises, making existing processes more efficient, or informing decision-making across the enterprise, data is flowing everywhere and its use seems limited mainly by our individual and organizational ability to harness it, to absorb, analyze and utilize it. It is still a symbol of power, but also a democratizing factor.
Guiding data well for the enterprise, creating a coherent and appropriate strategy for collecting, using and managing what is now a critical asset, is still a challenge. Some 7-8 years after “big data” emerged as a key topic, it is still a challenge to steward this asset in a way that furthers the business strategy, both capturing value in the present but also preserving the possibility of future value creation. Deciding what to share externally is arguably both more important and more of a challenge than ever. We will address these topics by discussing questions such as:
- What’s the case for having a data strategy? Is it simply now essential as part of a good business strategy, in essence a plan to ensure we are getting the most out of our data assets?
- What does it mean to have a good enterprise data strategy? How do you define this?
- What should a data strategy encompass? What are the key elements of a data strategy?
- Whose role is it to create this strategy? Who should lead? Who needs to be involved in the development of a good data strategy for your enterprise? How does a CIO go about getting full engagement for what was once perhaps viewed as “an IT topic”?
- What pieces should be addressed at the enterprise level and what at business unit or product or other levels?
- How do we proactively further the use of data to drive better decision-making in the organization with the speed (presumably faster?) appropriate to our business circumstance, yet with appropriate governance?
- What are the keys to good data governance and oversight? How do you implement this without making it stifling?
- How do we ensure access, taking advantage of the best aspects of data democratization and sharing to drive innovation, while simultaneously ensuring good hygiene and appropriately protecting intellectual property, PII, etc?
- What organizational steps should you take to support the flow, analysis and use of data?
- How do you deploy your data engineers and data scientists? Are they spread throughout the enterprise? In a center of excellence (CoE)?
- How do you spread data literacy and data usage ability across the enterprise? Is everyone now a data analyst to some degree? Does this need to be as widespread as the ability to use email if you want to maximize impact?
- What are the best ways to create wins to push progress in data strategy and management?
- What are the most useful ways to think about strategy/guidance/governance about data-sharing in the value chain / externally?
- What tools should play vital roles in our approach? AI/ML? Data visualization? What else?