On the 10th June, Sophie Gray, Director of Data & AI within Microsoft’s Customer Success Unit will be giving a keynote talk on the importance of a data-first culture followed by a fireside chat with myself on the practical approaches to building a data-first culture.
This event is hosted by the National Innovation Centre for Data and is part of their Data Insights series. You can find the link to register for the event at the bottom of this article.
I was lucky to speak with Sophie prior to the event to get an insight into the topics that will be discussed on the day. She initially joined the Microsoft Dynamics team but with the explosion of data and the growth of the MS Azure business, she followed her passion for business value and moved into the Cloud division where she now leads the AI Cloud solution architecture functions for the UK customer success unit.
What elements should be part of a data strategy?
To establish a common starting point, my first question was to ask about the key elements of a data strategy. Sophie highlighted four main areas:
· Business Strategy: concerns what capabilities clients have now, what they need in the future and how it aligns to the business goals.
· Organisational Roles: is about the who and the what, and how they think about being a data driven company.
· Data Architecture: includes security, reliability, operational excellence and tools and technologies being used.
· Data Management: covers governance and the values around ethics and responsibilities.
How should an organisation get started with implementing a data strategy?
I believe one of the most important aspects of any strategy is how you start its implementation. Sophie shared her perspective:
“The first factor is business strategy prioritising of the business outcomes (focusing on value and impact). Both looking at current projects and longer-term strategic initiatives. Combine business goals into a matrix with impact vs complexity.”
The second factor is to look at where you are on the data maturity curve / assessment. Benchmarking the current data estate and their capabilities and how this would lead to a roadmap, that Sophie categorised into three pillars, tactical, strategic and transformational.
What does a data-first culture mean to you?
Sophie shared her personal perspective on what a data-first culture means:
“A data-first culture fosters an open and collaborative participation across the organisation done consistently so everyone across the workforce can learn, communicate and help improve the company outcomes.”
The workforce backed by data can be more impactful at decision making and have greater influence within the organisation. Sophie also noted that the peak of maturity with the data-first culture is achieved when the client has organisation-wide frameworks and standards, together with data driven feedback loops.
We also talked about self-service reporting and how this is one of the outcomes with having a data-driven culture. Sophie concluded:
“With a mature data strategy there is a move from just data access to data-driven insights.”
How should a data strategy align with the Business strategy?
Sophie has already mentioned how the data strategy needs to align closely to the business strategy but also listed four pillars to unlocking transformation across the business to assess the impact and success of a data strategy.
1. Are you empowering your employees?
2. Are you engaging with your customers?
3. How are you optimising your business operations?
4. How does this help to transform your products?
What are the challenges which provide resistance to deploying a data strategy?
Sophie discussed two key challenges but acknowledges there are many others.
· People: Typically, are resistance to change from both technology and business users. Requires education and training to elevate the resistance and improve adoption towards new ways of working.
· Data: Lots of scattered and duplicate data within an organisation that causes practical problems for migration and modernisation.
Sophie emphasised that all organisations have a data strategy (even if it is not documented) – so they are already on the journey. Essentially the data strategy work never finishes, it just evolves with further technology advances and business benefits.
How do you see the data strategy supporting the AI strategy?
I have often heard clients talk about the inability to action an AI strategy until the data strategy is completed, so I was keen to hear Sophie’s opinion on this.
“Data strategy is the foundation for delivering the AI strategy.”
Sophie continued to state that a data strategy provides the foundation capabilities from data migration to data modernisation.
“Once these milestones have been delivered you can unlock digital transformation which ultimately gives strategic value back to the organisation.”
We agreed that you can overlay the data and AI strategy, while you need some of the foundational work from a data strategy, building AI driven insights allows business value to be realised quickly.
Finally, I asked Sophie if she had seen sustainable competitive advantage come from having a solid data strategy?
“Essentially data is helping the goals of ESG.”
Through providing key insights, data and analytics can drive an effective Environmental, Social and corporate Governance (ESG) strategy. As an example, allowing manufacturing to be conducted in a more environmentally friendly way is empowered by detailed data and analytics of the processes being used.
This has just given a sample of the topics we will cover during the Data Insights event on the 10th June. For more details and to register for free, please see here.
I would like to thank Sophie for her valuable time and for a very interesting conversation, covering some of the most important topics for businesses looking to create a data-first culture. I look forward to a more detailed discussion later this week