S3 | Ep 45 | The Data Strategy Canvass; Aligning Data Strategy with Business Objectives with Samir Sharma, CEO/Founder at Datazuum
Sep 12, 2023
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Samir Sharma, CEO & Founder of Datazuum, discusses aligning data strategy with business objectives. Topics include the Data Strategy Canvass, language barriers between business and data teams, the critical component of asking the right questions, the value discrepancy between business leaders and data teams, and the 7 steps to align a data strategy to business objectives.
Align the data strategy with the business goals by understanding the business strategy, assessing organization's capabilities, and developing a pragmatic roadmap.
Build relationships with key stakeholders, focus on business value and outcomes, and adopt an iterative approach to align the data strategy with business goals.
Deep dives
Aligning Data Strategy with Business Goals
When embarking on a data analytics or data strategy journey within an organization, it is crucial to align the data strategy with the business goals and objectives. This can be achieved through a seven-component process. Firstly, understand the business strategy by identifying its drivers, objectives, and goals. Then, align the data vision with the overall business vision, ensuring they are cohesive. Next, assess the organization's capabilities to identify any gaps and determine the use cases that will drive business value. Develop a business data model to understand how the business processes and decisions relate to data. Once these components are in place, focus on the operating model to determine the organization structure, ways of working, and cultural fabric that will support the data strategy. Prioritize the use cases based on cost-benefit analysis and return on investment. Finally, create a pragmatic roadmap that aligns with the business strategy and includes quick wins in the short term and long-term deliverables over the next three to five years.
Building Relationships and Seeking Support
Building relationships and seeking support are crucial aspects of successfully aligning the data strategy with business goals. Data leaders should aim to connect with key stakeholders, including the CEO, CFO, and other business leaders. It is essential to understand their drivers, objectives, and goals, and demonstrate how data can help achieve them. Building cross-functional partnerships with teams like finance can provide financial modeling support and help quantify the value of the data strategy. Data leaders should focus on developing relationships and seeking assistance from those within the organization who possess the expertise needed to fill knowledge gaps. By aligning with the business leaders and forming alliances, data leaders can establish themselves as valuable contributors and bridge the gap between data and business value.
Understanding Business Value and Outcomes
To ensure the alignment of the data strategy with business goals, it is crucial to understand the concept of business value and outcomes. Business value can be defined as the increase in revenue, the decrease in spend, or the reduction of risk. Data leaders should focus on identifying how the data strategy can contribute to these value drivers. They should frame the data strategy in terms of these value drivers, rather than solely focusing on technical aspects like data platforms or access to insights. Understanding the desired business outcomes and quantifying the impact the data strategy can have on these outcomes will help articulate the value and relevance of the data strategy to the organization.
Creating an Iterative and Results-Oriented Approach
To effectively align the data strategy with business goals, it is important to adopt an iterative and results-oriented approach. The seven-component process outlined earlier provides a framework for iterative development and continuous improvement. Data leaders should iterate through the process, seeking feedback from stakeholders and making adjustments based on their input and changing business needs. The focus should be on delivering tangible results by prioritizing use cases that align with business strategy, conducting cost-benefit analysis, and creating a roadmap that outlines short-term wins and long-term deliverables. This iterative approach allows for flexibility and ensures that the data strategy remains aligned with evolving business goals.
In Episode 45 of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is rejoined by, Samir Sharma, CEO & Founder of Datazuum, where they discuss how to really understand business objectives and align a data strategy that you can operationalise, which includes;
Defining, creating and operationalizing your data strategy
The ‘Data Strategy Canvass’ and the purpose of existence
The catalyst for creating it
Why business teams and data teams are talking different languages
The reasons why data strategies don’t often align with business strategies
Why asking the right questions is the critical component
How recent research has shown that only 6% of data strategies made any reference to business value generation
The 3 questions to answer about every use case
The difference between benefits and outcomes
Why many organisations don’t have clearly defined business strategies
How you can understand what the business objectives really are
Why you don’t need to be at the decision-making table to aligning data strategy to business strategy
The 3 buckets that all value levers are tied to in the eyes of “the business”
Why too many focus on data use cases and not business use cases
The value discrepancy between business leaders and data teams
Why most organisations don’t assess Data Leaders for the skills they actually need
Why reporting lines don’t matter
The 7 steps to align a data strategy to business objectives