How To Build Successful Business Cases as a Data Engineer

Your guide to crafting winning arguments for impactful data-driven decisions

Are you tired of your brilliant project ideas getting lost in translation or falling on deaf ears? As a data engineer, you may often struggle to secure the resources and support you need to bring your vision to life. Well, buckle up because I'm about to share a game-changing secret with you: the art of building a rock-solid business case.

In this article, you will master the craft of creating winning business cases. You will explore why a strong business case is your secret weapon, break down the essential steps to build one, and arm you with tips and tricks to make your proposal irresistible.

Oh, I almost forgot! A completed business case template is available at the end of the article.

So, let's dive in and unlock the power of persuasion! As you read the article, feel free to pause and reflect on how each step applies to your projects. This interactive approach will help you internalise and apply the concepts more effectively.

Reading time: 12 minutes

🖼️ Step #1: Background

This section is your chance to grab your stakeholders' attention. In a few short paragraphs, outline the purpose of your business case, the problem it solves, and the proposed solution. Show how your project fits with the company's goals.

So, how do you craft a background section that leaves your stakeholders wanting more? Start by putting yourself in their shoes. What are their pain points? What keeps them up at night? Use your insight to frame your project as the answer to their prayers.

To write an excellent overview, consider what's important to your stakeholders. Frame your project as the answer to their needs. Be clear and focus on the value your project brings. If you do this well, your stakeholders will want to read more.

Check these two examples. Which one is better?

Our Pandas data pipelines suck. They are too slow. I propose to rebuild them using Spark

or

By migrating our data to a scalable and efficient platform, we can reduce processing time by 30%, enabling faster decision-making and increasing customer satisfaction.

See the difference? In the second example, you outline the project and tie it to a larger business objective.

The background section is your chance to make a stellar first impression. So, make it count! Be concise, compelling, and laser-focused on the value your project brings.

🔥 Step #2: Problem Statement

Now that you've hooked your stakeholders with a killer overview, it's time to dive into the problem statement. This is where you show your understanding of the challenges your company faces. It's your chance to position your data engineering project as the solution.

To write a strong problem statement, clearly define the problem or opportunity your project addresses. Are there issues with your data systems? Are you having trouble with data quality or scaling? Use specific examples to show the real impact of these challenges on the business.

Don't just stop at a high-level description – use specific examples to illustrate the real-world impact of these challenges. Here’s a short example of a problem statement:

Our current data pipeline takes 8 hours to complete, resulting in delayed reporting and missed opportunities for timely decision-making. This has led to a 15% drop in customer satisfaction scores and a 10% increase in customer churn.

Providing concrete examples makes the problem tangible and relatable to your stakeholders. They can see the direct link between the technical challenges and the business outcomes they care about.

But don't just focus on the problem. Use the problem statement to introduce your proposed solution. Hint at how your project solves these issues and leads to a better future.

The problem statement is your chance to create a sense of urgency. You must convince your stakeholders that maintaining the status quo is not an option.

Make the problem clear and connect it to business outcomes. This will make your stakeholders eager to hear about your solution.

📅 Step #3: Project Description

In this section, you dive into the details of your proposed solution. Here, you need to show them exactly how you plan to solve the problems you outlined.

Start by defining the scope of your project. What are the boundaries of your solution? What data systems and technologies do you plan to use? Be specific so your stakeholders understand what's involved and what resources you'll need.

Next, explain the technical approach. Describe the architecture of your solution, including data flows and critical processes. Use diagrams to make it easy to understand.

But don't just focus on the technical details – tie them back to the business benefits. For example, you could say

By implementing a distributed data processing framework, we can parallelise our data pipelines and reduce processing time from 8 to 2 hours. This will empower business users to make data-driven decisions faster.

Include the project timeline and milestones. Your stakeholders want to know how long this should take and what they can expect along the way.

Break your project into phases and highlight the deliverables at each stage. This will give stakeholders a sense of progress and help them plan.

Phase 1 will focus on data ingestion and storage and is targeted to be completed in 3 months. By the end of this phase, we will have a centralised data lake in place, ready to support the subsequent stages of the project.

The project description is your chance to showcase your expertise and excite your stakeholders about the possibilities. Use clear language, compelling examples, and visual aids to make your solution come to life. By the end of this section, your stakeholders should be excited to see your vision become reality.

🧭 Step #4 Strategic Alignment

In this section, show your stakeholders how your project fits into the big picture and demonstrate that you understand the company's broader goals.

So, how do you make strategic alignment crystal clear? Connect your data engineering project to the company's key objectives. Are you supporting digital transformation? Improving customer experience? Boosting efficiency?

Start by identifying the specific business objectives that your project supports. For example, you could say:

This project aligns with our strategic goal of becoming a data-driven organisation by modernising our data infrastructure. It will enable us to harness the power of our data assets, gain deeper insights into customer behaviour, and make informed decisions that drive business growth.

But don't just stop at a high-level statement – dive into the details. Show how your project will drive progress on company objectives. Use metrics and KPIs to quantify the expected impact and make it tangible for your stakeholders.

Feel free to think big and showcase how your project can give your organisation a competitive advantage. Highlight how your solution differentiates your company and position it for long-term success.

Tie your project to the company's strategic objectives and show its concrete impact. This makes a strong case for why your project deserves to be approved.

🤑 Step #5: Benefits and ROI

It's time to discuss the bottom line—your project's benefits and ROI. In this section, demonstrate the concrete value your project will deliver. Quantify the expected cost savings, revenue growth, and risk reduction benefits.

But how do you go about putting a number on those benefits? Use data and analytics to support your claims. Look at the metrics that matter most to your company and show how your project can improve them.

For example, if you're proposing a data pipeline optimisation project, you could say:

By streamlining our data processing, we expect a 30% reduction in processing time, saving $50,000 per year in infrastructure and personnel costs.

But don't just focus on cost savings. Consider how your project would drive revenue growth, too. This will help stakeholders understand the financial impact and plan accordingly.

This project will empower our sales team to identify high-value leads and tailor their pitches accordingly. We estimate a 15% increase in conversion rates, resulting in an additional $200,000 in annual revenue.

By the end of this section, your stakeholders should be eager to give you the green light and see those benefits come to life.

💸 Step #6: Cost Estimate

It's time to discuss the elephant in the room—the cost of your project. In this section, your cost estimates need to be clear, detailed, and justified. Your stakeholders want to know precisely what they're signing up for and how much it costs.

Provide a full breakdown of all the costs for your project. Include hardware, software, personnel, and any other resources you need.

Justify each cost by linking it to specific project activities and deliverables. Don't just list numbers. Explain why each cost is necessary.

A bad example of a cost estimate is:

Data processing platform: $100,000.

This one is far better:

We need a scalable data processing platform to support the increased data volume. We recommend Platform X, which costs $100,000. This includes installation, configuration, and training for our team.

Here's a pro tip – Consider using a phased approach to show how costs will be spread over time. This helps stakeholders understand the financial impact and allows them to plan accordingly.

For instance, you could say:

The total project cost is estimated at $50,000, broken into three phases. Phase 1, which focuses on data ingestion and storage, will require an investment of $20,000 in the first quarter. Phase 2, which involves data processing and analytics, will cost $15,000 and span the second and third quarters. Finally, Phase 3, which includes data visualisation and reporting, will require $15,000 in the fourth quarter.

By providing a phased breakdown, you give your stakeholders a clear picture of the financial commitments and help them allocate resources effectively.

Be transparent and build trust with your stakeholders. Justify your expenses and use a phased approach to make the financial impact manageable. By the end of this section, your stakeholders should know what they're investing in and why it's worth it.

☂️ Step #7: Risk Assessment and Mitigation

In this section, you'll address your project's potential risks. Identify risks and present solid plans to handle them. This will show your stakeholders that you're realistic and ready to tackle challenges.

Put on your risk management hat and think critically about the potential obstacles that could derail your project. Consider technical challenges, data security concerns, and dependencies on external vendors.

Assess the likelihood and impact of each risk and provide clear, actionable steps to mitigate it. For example, one of the risks you've identified is the potential for data quality issues during the migration process.

Don't just say:

Data quality issues may occur.

Instead, dive into the specifics and present a plan. You could say something like:

Due to the complexity of the data sources, there is a medium risk of data quality issues arising during the migration process. To mitigate this risk, we will implement a robust data validation framework that includes automated data quality checks, data profiling, and manual spot checks. We will also allocate a dedicated data quality assurance team to monitor the migration process and address any issues promptly.

Address any assumptions or constraints that could affect your project's success. Be transparent about the factors you're relying on and the limitations you're working within.

This project assumes that the source systems will be available for data extraction during the designated migration window. Any unforeseen outages or delays could impact the project timeline. To mitigate this risk, we will work closely with the system owners to ensure proper communication and contingency plans are in place.

By acknowledging assumptions and constraints, you show your stakeholders that you've considered all angles of the project and are prepared to adapt as needed.

Be thorough, specific, and ready to tackle any challenge. By the end of this section, your stakeholders should have confidence in your ability to handle risks and deliver success.

🚧 Step #8: Implementation Plan

In this section, create a clear plan demonstrating your project management skills and covering all the bases.

Explain the project management approach you'll use. Describe how it will help you deliver the project efficiently.

Define the project team structure. Outline each team member's roles and responsibilities. Show how their skills align with the project's needs.

Provide a detailed timeline with key milestones and deliverables. Break the project into manageable phases. Assign clear owners and due dates for each task.

Describe your communication and reporting plan. Explain how you'll keep stakeholders informed of progress and issues. Set expectations for regular status updates and meetings.

Outline your change management approach. Identify the groups impacted by your project. Describe how you'll prepare them for the changes and ensure a smooth transition.

And that wraps up your business case. Now, let me give you some more tips and tricks.

🤓 Tips and Tricks

Sell Your Project Upfront 🕛

You can't just throw a business case at your boss and expect them to accept it. You need to sell your work to them before presenting the document. Tell them about it long before the implementation time comes. The business case should be your last step in the “selling” process, not the first one. Make sure what you want makes sense.

It’s Not About You 👞

Forget about all the fancy tech. Demonstrate how your project aligns with the broader strategic goals of the organisation. C-level executives are always looking for how specific projects can fit into the larger picture of the company's future. Put yourself in decision makers’ shoes to craft a compelling business case.

Keep It Concise and Direct 🚀

While details are necessary, keep your document concise and to the point. High-level managers often prefer high-level summaries with the option to delve into more information if required. I rarely have a document over 5 pages; most don’t exceed 3 pages.

🏁 Summary

Building a winning business case is crucial for getting your data engineering projects approved and funded. Following the critical sections outlined in this article can create compelling proposals that resonate with your stakeholders.

Remember to start with a solid executive summary that grabs attention and highlights the value of your project. Clearly define your problem and how your solution aligns with business goals. Provide a detailed project description, cost estimate, and implementation plan to show you've thought through every aspect. Remember to address risks and define success metrics to build trust and confidence.

So, what's next? It's time to put your newfound knowledge into action. To help you get started, I've created a handy example that you can use as a guide for your next business case.

By mastering the art of business case development, you'll be able to secure the resources and support you need to drive impactful data engineering initiatives.

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📚 Picks of the Week

• Your business case is great. Stakeholders agree you should work on it. But they want you to prioritise something you hate first. What do you do? Read this great piece by

  Amy Mitchell
  . (link)

• Julien Hurault
  came up with a crazy idea to use Snowflake as an expensive supercharged Lambda. (link)

• Are you looking for a new BI tool? Olga from

  Data Analysis Journal
  listed some interesting data viz tools, and I personally would love to test some of the newer ones. (link)

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