Are you aligned with your stakeholders on the data-driven business problem

In a previous article, I shared the results from a survey I conducted to understand the biggest challenges Data Scientists face when it comes to Data Storytelling and collaborating with business stakeholders to successfully execute data science projects. 

As a reminder, based on the survey, the biggest challenges Data Scientists face when it comes to collaborating with business stakeholders are: 

1. Difficulty influencing decision making with data insights (30% of responses)

2. A lack of stakeholder confidence or trust in the analysis (23% of responses)

3. Stakeholders not clearly defining their business problems or objectives (23% of responses). A different way to say this would be a lack of alignment between data scientists and stakeholders on the business problem

Clear alignment with business stakeholders on the business problem actually increases confidence in the analysis and makes it easier to drive decisions with data. Therefore, in this article, I’ll break down why stakeholder alignment matters, and how you can achieve it.

Why stakeholder alignment on the business problem matters

A lot of data science projects fail or aren’t as successful as they can be because enough time is not spent at the start of the project to iron out the business problem and context.

For example, a data scientist working in a health insurance company might receive a request to build a model to predict which customers are likely to be admitted to the hospital. Those customers would then receive care intervention to prevent the admission. 

This project request might sound straightforward enough so the data scientist jumps right into building the model only to realise after completing it that there are actually two types of admissions:

• A planned admission, initiated by a doctor (for example, a scheduled hip replacement surgery)

• An unplanned admission (for example, an emergency admission due to uncontrolled diabetes)

And that this model should have actually accounted for only unplanned admissions because those can possibly be prevented through proactive care intervention. If the data scientist had had further engagement with the business stakeholders before building the model to iron out the business problem and context, this detail would have surfaced thus allowing for a more tailored and appropriate model to be built. This is why clear alignment between data scientists and stakeholders on the project context is critical when starting a project. It ensures that the right or best solution is developed which boosts stakeholder confidence in your analysis and ultimately makes it easier to drive decision making with your data insights.

How to align with business stakeholders on the business problem

Below are some questions to ask to help you align with your stakeholders on the business problem:

• What problem do you want to solve? 

• Why do you want to solve it? 

• What data insights / metrics do you need to solve the problem?

• How will the results be used?

If you would like to learn more about effectively collaborating with stakeholders to drive the success of your data science project, be on the lookout for my upcoming virtual Data Science Masterclass for Junior Professionals and Students In Training, now open to participants globally.