As companies progress on their journey towards data maturity, the role of the Data Strategist becomes even more important. These new technical business experts must master increasingly specialized skills in bridging the gap between strategy and data science.
We wrote about The Rise of the Data Strategist in 2019 and 2020. We argued that organizations cannot rely solely on unicorns – data professionals who possess all the necessary technical and business skills. Today, the Data strategists are the interface between business and technical data teams, allowing each side to focus on their core competencies. They have become the glue that holds the data-driven machine together.
The Growing Complexity of the Data Strategist’s Role
Some years later, and in the wake of a global pandemic, the demand for skilled Data Strategists has intensified, and the debate developed on several fronts.
During the pandemic, we saw organizations trying to accelerate their data transformation, leading to an increased demand for talent in this field. At the same time, the academic offering cannot match the speed in which the demand develops. This leaves organizations in a difficult position.
Experienced talent is scarce and expensive, while the skills required to execute an effective Data Analytics Strategy have further developed across all data domains.
"Just as with the recent specialization of data science roles along multiple dimensions, we foresee a similar trend for the role of data strategists. As companies become more mature on their data journey, a mix of multiple strategist profiles will be needed to scale data capabilities. "
Dirk Hofmann, Co-Founder and CEO of DAIN Studios Germany.
The Data Strategist’s job description
A Data Strategist’s job description often includes responsibilities such as developing and implementing a data-driven strategy that aligns with the business objectives.
For deeper analysis, we regularly identify three distinct profiles of Data Strategists, each with a unique focus:
- Those leading data & AI transformations from a strategy perspective
- Those that are responsible for translating this strategy to the operational level, and
- Those that work closely with technical teams to deliver data products (for internal or external use).
Some are expected to bring transformational changes, others focus on contributing with incremental impact. Some must have their strengths in conceptual thinking and communication, while others need to bring executional excellence. None are more important than the others but having a good mix of these different talents is key to data-driven success.
Relentless specialization has brought us back full circle to the old problem of Data Scientist: it is still possible to find the right people for the job, but it will become ever more difficult.
The 3 Key profiles of Data Strategists and Key responsibilities
1. The Transformation Leader
As a Transformation Leader, the Data Strategist is responsible for leading large-scale data transformations that align with the company’s overall business strategy.
This role is integral to shaping and executing the company’s data-driven strategy. It often overlaps with or directly assumes the responsibilities of a Chief Data & Analytics Officer (CDAO) or an Analytics Lead.
The Transformation Leader’s key responsibilities include:
- Defining and executing the data strategy’s with all its critical enabler.
- Driving value-driven project portfolios
- Promoting and building a data-driven culture
- Facilitating communication across the organization.
The Transformation Leader ensures that the entire data organization is aligned and successful in achieving strategic goals.
2. The Operation Leader
Operation leaders must be ready to bring the data strategy home by translating it to a tangible operating model and helping to establish robust data governance.
As the size of data organizations grows larger and larger (including Citizen Data Scientists embedded in business functions), they are responsible for designing an operating environment that is built for the needed scale both in terms of data, tools, and processes.
Daily work ranges from creating logical data assets, setting up the governance structure, all the way to defining tasks, roles and responsibilities for the data development and operations processes. They play a crucial role in bringing companies out of pilotitis – a constant state of experimentation with data & AI.
Operation Leaders play a critical role in bringing data strategies to life by translating them into tangible operating models. They focus on implementing the company’s data analytics strategy by establishing robust data governance and ensuring scalability.
The Operation Leader’s key responsibilities include:
- Creating logical data assets and setting up governance structures
- Defining tasks, roles, and responsibilities within the data organization
- Transitioning the company out of a constant state of experimentation into sustainable, scalable operations.
The Operation Leader ensures that the organization moves beyond pilot projects and embeds data-driven processes into everyday operations.
3. The Product Owner
The Product Owner in the data realm focuses on the business success of specific data projects or products. This role is crucial for ensuring that data projects align with the company’s strategic objectives and deliver measurable value.
The Product Owner ‘s Key responsibilities include:
- Managing requirements and priorities for development teams.
- Facilitating communication between business and technical teams.
- Promoting the data product internally and externally.
- Ensuring that integrations are in place to generate organizational value.
The Product Owner ensures that data initiatives are not just technically sound but also strategically aligned and impactful.
Further specialization on the horizon
The good news is that further specialization within the role of Data Strategist does not necessarily require creating new corporate functions. All three profiles share a common goal: bridging the gap between data professionals and the business side.
Each profile requires a mix of similar skills, albeit in different concentrations:
- Technical data and technology expertise
- Domain knowledge within the company’s industry
- Effective communication skills
- Strategic thinking
- Product and project management experience
- Operational know-how
Crucially, this means a Data Strategist can be trained to embrace a sub-profile, though perhaps no longer be the only data strategist aboard.
Over the next years, Data Strategists will need to continually expand their skill sets to include areas such as data management and data governance, which are increasingly important in executing a comprehensive data-driven strategy.
The role of the Data Strategist has always been about building bridges and connecting the dots: between business and IT; between strategy and execution. As new challenges arise, these bridges will require even more specialized expertise.
There will still be a role for generalist Data Strategists – and people who can master all skills will rise faster than others. However, companies should prepare for the reality that finding the right specialized Data Strategists will become more challenging in the years ahead.