Successful implementation of a model goes far beyond the technical intricacies of model selection and data analysis — it encompasses effective stakeholder management. Think of ‘Stakeholder Management’ as tailoring the process to the people involved. The goal is to ensure that your model is doing what it needs to do, and you continue to bring value. How you tailor the process and output depends on the needs of the stakeholders, whether this is executives, managers or consumers. It’s all about delivering actionable insights that enable them to make informed decisions.
As a data scientist, your worth is often determined by how well you translate your technical insights into real-world decision-making. This is both a blessing and a curse to most of us — soft skills are notoriously undervalued in technical fields, but acts as the bridge between our mind-crunching work and the value than can be derived from it. While technical skills are important for the foundation for our work, your ability to communicate effectively, empathize with stakeholders, and drive action is what truly elevates our impact. Communication is the single most important skill as a data scientist, yet it is stereotypically also the most difficult to acquire.
Below are some actionable tips that can help in effective communication:
1. Tailoring model selection
Choosing the right model goes far beyond identifying the most accurate algorithm.
It’s true that black-box models can be the most accurate and engaging for us Data Scientists, but they’re often not transparent or easily interpretable, making it hard for stakeholders to trust the results. This is where it may be better to opt for simpler models like ARIMA or Exponential Smoothing where you may decrease accuracy but increase interpretability. It is always best to do research on the various models that exist.
Here’s an example of some of the most common forecasting models and their interpretability;
2. Clear Visualisations
Present your results in a way that resonates with your audience.
Think about well-designed charts, graphs, and dashboards. This involves clarity, simplicity, and relevance to the audience. How can you help stakeholders grasp key insights quickly and make informed decisions?
There are numerous articles and courses online that help in data visualisation!
Executives might favour high-level dashboards, while managers might require detailed reports with error metrics. Consumers typically benefit from clear and actionable visualizations that translate forecasts into practical applications.
Personally, I take a lot of inspiration from Prophet’s base visualisations as it clearly depicts the actual values vs the model predictions. I usually add annotations or highlight certain points (both future and past) for significant moments.
3. Storytelling
Don’t just present data; tell a story. Highlight the context, key findings, and potential implications of your forecasts. Understand your audience and frame the narrative in a way that is relevant to the specific goals and challenges.
Focus on the “Why” before the “How”
- What is the overall objective you’re trying to achieve with the forecast
- How will the forecasts be used to inform decision-making?
- What are the potential consequences of inaccurate forecasts?
- Acknowledge the limitations and uncertainties in the model’s predictions
Highlight the Journey, not just the Destination
- Always tie in the journey to the main task at hand.
- Share key challenges you encountered during data pre-processing or model selection and how you overcame them.
- Highlight any unexpected insights you discovered along the way.
Make it Relatable and Actionable
- Speak the language of your audience.
- Quantify the potential impact of your forecasts on metrics like revenue, cost savings, or resource allocation.
- Offer clear recommendations and actionable steps stakeholders can take based on your insights.
Remember, the key to successful forecasting goes far beyond the accuracy of the model, to its ability to empower stakeholders to make informed decisions. Time-series forecasting is a powerful tool, so use it wisely and carefully!
Unless otherwise noted, all images are by the author.