The two main forces in data analytics are converging to cause organizational confusion and inefficiency. The first is simple and well known: the rise of more datasets, larger datasets, and more diverse datasets, developed internally and procured. The second is a rise in the complexity of processes to both harmonize and analyze data. Even before generative AI and black-box large language models made their way into business processes, predictive analytics and equally opaque machine learning processes were driving more decision making. These advanced analytics capabilities were coming for every part of the business, because the expertise was available and the desire for fresh insights and efficient processes was ripe. When the two patterns persist, the outcome is a widening gap between producers of analytics and consumers of it within an organization.  

What is a Business Translator? 

Smart companies are built on diverse skillsets and segmented responsibilities. Of course, at the individual level, we all want to be able to speak the language of the c-suite and the data engineering team but that isn’t practical or feasible for everybody. There needs to be individuals specifically in positions to move fluidly from technical to business language. This has given rise to the role of the business translator. This individual has the background to understand the depths of processes required in the given analytical application or data domain but also understands why certain questions are being asked of the data and how the answers will be used.  

Why is Business Translation Important in the Context of Analytics Projects? 

In analytics projects, the role of a business translator is pivotal because of the pitfalls that can arise when communicating from stakeholder to technical team and visa-versa. Business stakeholders may know what they want but struggle to communicate the details in a way that technical teams can execute effectively. With AI, the gap in expectations can widen even greater. Translators help bridge this gap by ensuring that the “what” and “why” of business needs translate into “how” technical teams can deliver. They can also track business needs past the layer of individuals that businesses directly interact with (maybe the data scientists) towards all the back-end teams required for successful analytics – think data engineering, various parts of the IT org, etc. They also help articulate value from the technical team. This prevents an undesired outcome where the team’s hard work has uncovered something meaningful in the data, but it is disregarded purely due to a lack of understanding. Preventing this misalignment not only saves time and resources but also ensures that analytics projects deliver actionable insights and measurable value to the organization. 

Analytics projects are particularly vulnerable to gaps in communication because they often operate in environments that are less structured or mature. Many organizations are still building their data capabilities, and analytics projects are not always governed by clearly defined processes. Oddly, more advanced processes in ML/AI are even less governed than more historical, defined reporting. As a result, business translators play a crucial role in facilitating alignment between all parties involved. They help ensure that business objectives are achievable within the constraints of the technology and available data, creating a smoother pathway for execution.  

Who Can Be a Business Translator? 

Business translators can come from a variety of backgrounds. In some cases, the role may be filled by a skilled product manager, someone on the business side who has a deep understanding of the data domain, or even a data scientist with strong communication skills. This flexibility in the role is both a strength and a challenge. On one hand, it means that the translator role can be adapted to the needs of the project and team. On the other hand, it also means that the role can be overlooked entirely, especially if it isn’t explicitly defined from the outset of a project or during team formation. Just “gathering requirements” is no longer enough to extract value from analytics initiatives. 

While it isn’t always necessary to have a dedicated full-time business translator, it’s crucial that someone on the team fills this role. Without this role, teams often face misaligned priorities, unclear objectives, and communication breakdowns, all of which lead to inefficiencies and missed opportunities. As analytics projects grow more complex, having someone with both technical understanding and business acumen becomes indispensable. 

How does the Business Translator Role Vary? 

The duties of a business translator are shaped by both the specific project phase and the organization’s level of maturity. In early-stage projects, their focus is on defining questions that align with actual business value and guaranteeing those questions translate into actionable, technically feasible solutions. During development, they act as a bridge, ensuring that the technical output remains connected to the business’s needs and preventing teams from veering off course into the land of over-complicated solutions. At the testing phase, business translators are crucial for verifying that outputs pass more than just a technical audit. Do the results make sense in the real world? Will they drive decisions that matter? And finally, in deployment, they monitor ongoing performance, helping the team spot opportunities for improvement or automation and flagging potential risks like model drift. 

The business translator’s role evolves depending on the organization’s maturity level. In less mature organizations, they may spend more time setting clear metrics, helping to establish a consistent communication framework. In more mature companies, their role might focus more on refinement, optimization, and ongoing alignment as the project evolves. 

Ultimately, having a business translator as part of the team provides crucial oversight and helps ensure that analytics projects deliver tangible business value.  

Clarkston’s team of experts have the deep experience to act as business translators in analytics projects and can also enable individuals on your teams to play this crucial role. To learn more, connect with us today. 

Contributions by Christian Pierce and Nathan Keliher