Talk Techie to Me: Translating Data Complexity for Business Leads
Bridge the gap between data engineering and business strategy. Discover practical techniques to communicate your insights in a way that drives decision-making.
Greetings, curious reader,
Communication between data engineers and business stakeholders can make or break projects. While technical skills are crucial, your ability to translate complex concepts into business value often determines success. Many data engineers struggle to bridge this gap effectively.
You'll position yourself as more than just a technical expert by mastering essential communication techniques. You'll become a valuable partner who can articulate the business impact of data engineering work. This article will equip you with strategies to enhance communication and deliver data products that genuinely resonate with stakeholders.
I'll guide you through speaking the language of value, using simple analogies, and maintaining transparency about project timelines and challenges.
Reading time: 8 minutes
The Cost of Poor Communication
I've had the privilege of working with brilliant data engineers throughout my career. Their technical skills were far better than mine. However, I've witnessed many of these talented individuals be passed over for promotions due to a single flaw: their inability to communicate effectively with stakeholders.
In meetings with business leaders, these engineers would enthusiastically discuss Kafka, data streams, and other technical intricacies. The result? Confused looks and needing someone else to translate the information. This communication gap hindered their career progression and reduced the perceived value of their work.
I found you only need 3 practices to level up your game when talking to stakeholders. Now, keep in mind that I primarily mention business people like your Head of Marketing. However, this is also valid for technical people like Directors of Engineering.
Practice #1: Speak the Language of Value
When you speak the language of value, you build trust with stakeholders. You help them understand why your work matters. You create allies who champion your projects by framing discussions around business impact.
How to Implement
Focus on how your data efforts impact the bottom line. Do they save money? Increase efficiency? Improve decision-making? Always explain the “so what” behind your tasks and milestones.
Consider this scenario: You've optimised a database query. Instead of discussing technical details, highlight how this speeds up reporting. Explain how faster reports lead to quicker decisions and potentially increased revenue.
Ask yourself: How does this task contribute to our business goals? What problems does it solve for our stakeholders? By answering these questions, you'll naturally speak their language.
Remember, stakeholders care about outcomes, not processes. They want to know how your work drives the business forward. Can you quantify the impact? Even ballpark figures can be influential.
Try this exercise: Write down your current project's technical goals. Now, reframe each one in terms of business value. This practice will help you communicate more effectively with non-technical team members.
Practice #2: Use Analogies and Simple Language
Analogies make complex concepts relatable. They reduce misunderstandings and help stakeholders grasp technical ideas quickly. By avoiding jargon, you create an inclusive environment where everyone feels comfortable contributing.
How to Implement
Think about your stakeholder's domain. What concepts are they familiar with? Use these as jumping-off points for your analogies. For example, if you're working with marketing teams, you might compare data pipelines to marketing funnels.
Here's a simple analogy for explaining data warehousing:
Think of our data warehouse as a library. We're organising all our company's information in one place, making it easy to find and use when needed.
Avoid technical terms unless specifically asked. Instead of saying, "We're implementing a new ETL process", try "We're building a system to gather and organise our data more efficiently."
Frame discussions around outcomes. Rather than detailing how you'll build a machine learning model, explain how it will help predict customer behaviour and boost sales.
Practice explaining your work to non-technical friends or family. Can they understand it? If not, simplify further. This exercise will sharpen your communication skills.
Practice #3: Be Transparent About Roadblocks and Timelines
Transparency keeps stakeholders informed and prevents surprises. It encourages collaboration and proactive problem-solving. When you're open about challenges, you build trust and demonstrate your commitment to the project's success.
How to Implement
Update stakeholders regularly on progress. Focus on business outcomes rather than technical details. For example:
We're 60% through the project. Once complete, you'll be able to access real-time sales data.
Share blockers in simple terms. Instead of diving into technical issues, say something like:
We're waiting on access to a crucial data source. This might delay our timeline by a week.
Don't hesitate to ask for support when needed. Be specific about what you need. For instance:
Could you help us prioritise this data integration with the finance team? It's key to delivering accurate forecasts.
Create a simple project dashboard. Use visual aids like progress bars or milestone charts. These tools help stakeholders quickly understand where things stand.
Transparency doesn't mean overwhelming stakeholders with information. Provide high-level updates and offer more details if requested.
Combining These Practices for Maximum Impact
By integrating these communication strategies, you'll create a smoother project experience. You'll align expectations, reduce misunderstandings, and facilitate quicker decision-making.
Imagine this scenario: You're leading a data lake project. You explain its value in terms of faster insights and better decision-making. You use analogies to describe its structure and function. You're transparent about the timeline and potential roadblocks.
What's the result? Stakeholders understand the project's importance. They're more likely to support you when challenges arise. They can make informed decisions about resource allocation and priorities.
These practices set you apart as a leader in data engineering. You're a valuable business partner who can bridge the gap between data and strategy.
Overcoming Challenges
You'll encounter various communication challenges. Some stakeholders may want deep technical dives. Others might glaze over at the mention of data. How do you navigate these differences?
Start by asking questions. Understand each stakeholder's background and interests. Tailor your communication style accordingly. For technical enthusiasts, prepare more detailed explanations. For big-picture thinkers, focus on outcomes and business impact.
Consider creating different versions of your updates. A high-level summary for executives and a more detailed breakdown for team leads. This approach ensures everyone gets the information they need.
Remember, flexibility is key. Be prepared to shift gears mid-conversation if you sense your approach isn't resonating. Pay attention to body language and engagement levels.
Don't be afraid to ask for feedback on your communication style. This shows you're committed to improvement and value the stakeholder's perspective.
Another practical approach is the BLUF (Bottom Line Up Front) method. This technique involves presenting the most important information first, followed by supporting details.
Start your communications with the key takeaway or decision point. Then, provide a brief explanation of the context and implications. For those interested in the technical aspects, you can include these details at the end of your message or in an appendix.
I've written an in-depth article about the BLUF method and its applications in data engineering communication. It's a powerful tool that can significantly improve your ability to convey complex information effectively.
Practical Example: Turning Data Jargon Into Business Insight
Let's walk through a real-world scenario. Your team faces a delay in delivering a data pipeline project due to integration issues. How do you communicate this effectively?
Tech Talk:
We've hit a snag with the ETL process because the PostgreSQL schema has changed, and we need to refactor the pipeline logic to accommodate the new structure.
Stakeholder-Friendly Talk:
The system we're pulling data from has been updated. We need to adjust our tools to work with this change. This will delay the project by two days, but we'll still deliver by the end of the week. This adjustment will ensure you get the most accurate and up-to-date insights.
Let's break this down:
You contextualised the technical issue in business terms.
You explained the impact on delivery timelines.
You offered a clear solution and path forward.
You highlighted the benefit of making this adjustment.
This approach keeps stakeholders informed without overwhelming them with technical details. It demonstrates your problem-solving skills and commitment to delivering value.
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Final Thoughts
As a data engineer, your ability to speak the language of business is a superpower. It transforms you from a technical resource into a strategic partner. Focusing on value, using simple language, and maintaining transparency will build stronger relationships with stakeholders.
These communication skills are as crucial as your technical abilities. They help you advocate for your projects, secure resources, and ensure your work has maximum impact.
Challenge yourself to improve your communication skills alongside your technical ones. With practice, you'll become an indispensable bridge between the world of data and business.
Summary
We've explored three key strategies for effective communication:
Speak the language of value: Frame your work in terms of business impact.
Use analogies and simple language: Make complex concepts accessible.
Be transparent about timelines and challenges: Keep stakeholders informed and engaged.
By implementing these approaches, you'll enhance your effectiveness as a data engineer. You'll deliver projects which truly meet business needs and build strong, collaborative relationships with stakeholders.
How will you adjust your communication style? Which of these strategies resonates most with you? Remember, effective communication is a skill. Like any skill, it improves with practice. Start small, be patient with yourself, and watch as your influence grows.
What is your next step? Choose and apply one of these strategies in your next stakeholder interaction. Pay attention to the response. Did it improve understanding? Did it lead to better collaboration? Use these insights to refine your approach further.
By mastering the art of translating data engineering into business value, you'll advance your projects and career. Are you ready to take your communication skills to the next level?
Until next time,
Yordan
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Also, a nice trick is combining a TL;DR with some Smart Brevity (why it matters) techniques when doing announcements or regular updates. Good one Yordan! 🙌