Budgeting is easy for fixed costs and relatively simple for variable costs, as long as you know the drivers of the variable expense, such as number of products sold or parcels shipped.
For strategic investments in capabilities like Data Science and Data Engineering, budgeting can be more difficult, especially if you do not currently have full-time staff devoted to the function. If you have ideas about the type of outcomes you want to drive using data and a high-level understanding of the complexity involved in implementing those ideas. With those two things, you have everything you need to get a rough estimate of your data science and data engineering budget for 2021. Just use the framework below.
We propose two metrics, ranked 1-5 with 1=low and 5=high, to frame your conversation about budget for data projects:
At this level, there is no need to consider the actual dollar amount of revenue or cost driven. All you want to consider is the relative impact and complexity of different data-driven initiatives your company could consider.
Create a spreadsheet that mirrors the below (Feel free to use this template):
For questions you can use to assess impact and complexity, please use the appendix to this article.
Once you have your scores assigned for each project, you can plot the impact vs. complexity of each data project. Prioritize the projects in the bottom right corner, those with high impact and low complexity, followed by those in the top right, those with high impact and high complexity. At that point, you can start to dive deeper into the details of budgeting for those projects.
After prioritization, take each of the projects you have decided to prioritize, and make a quick attempt to estimate the potential value of the project to your company.
To understand project value, you will need to do the important work of determining how your company will use the output of the project:
Once you understand the project’s value, you can take the budgeting process in two directions:
A good partner will also be able to help you understand the best way to structure a project to capture maximum value. Oftentimes, multiple value propositions from separate projects can be captured with a minimal increase in the scope of a single project. Automated reporting on ad spend and product profitability, for example, both involve a data pipeline, data warehouse, and business intelligence suite.
With projects prioritized and the costs and benefits of data projects estimated, you should have the confidence you need to secure a budget for the highest priority data projects you need to grow and optimize your business in 2021.
The CorrDyn team can guide you through either the experimentation-based approach or the assessment-based approach.
If your company wants to move quickly with the experimentation-based approach, we can leverage our experience to guide your project toward the highest ROI proof-of-concept that can be achieved in the shortest period of time. We excel at delivering proofs of concept early in each engagement to build trust in the ROI of the solution being developed.
If your company wants to use the assessment approach to understand the full scope of work to be completed, CorrDyn begins the engagement with an assessment to develop the project plan and help you estimate the cost of the solution proposed. If you are considering embarking on data projects in 2021, we can help you estimate the return and investment required for each project.
We want our data projects to deliver value, and we are prepared to be your long-term technology partner. We will not begin an engagement without confidence that the project will deliver strong ROI for your business and can show you the path to success.