ROI

How to calculate ROI for data discovery

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What is the opportunity cost of data debt?

The cost of data debt is an important metric to consider when evaluating the value of data within an organization. It represents the average cost of time spent by data engineers and analysts on data discovery and organization. Assuming an average salary of $75k, a team of 10 data engineers and analysts, 25% of their time spent on data discovery, and another 25% of their time using bad data - the cost of data debt to a business could exceed $375,000/year.

You can measure the financial impact of data debt by looking at how much money it costs your team to discover and use bad data.

How to calculate the ROI of data discovery:
Cost of data debt = (% of time spent discovering data + % of time spend using bad data) * (resource cost)

Step 1: Calculate how much time is spent discovering data. On average, most data teams spend over 25% of their time discovering and preparing data.

Step 2: Calculate how much time is spend using wrong data as a result of poor documentation and incorrect dashboards. On average, most data teams spend at least 25% of their time using and fixing bad data.

Step 3: Calculate the resourcing cost of everyone who uses data. This includes data practitioners as well as end consumers of data products.

The cost of data debt can vary significantly depending on the amount of data collected, the number of employees who access data on a regular basis, and the state of data documentation and management. Additionally, the cost of data debt may be more pronounced during periods of business change, such as hiring or a business model shift.

The cost of data debt factors in the opportunity cost of organizing or discovering data, or the cost of using the wrong data. Having analysts who don’t have to spend as much time finding the right information and engineers that can manage data easily can help teams take on more projects that help demonstrate the value of the data function. Additionally, having data that employees can trust is a massive benefit to an organizations productivity.

By having an idea of the cost of data debt, teams can more easily calculate their return on investment for a data enablement tool. Understanding the cost of data debt is essential for data teams to demonstrate the value of their work and to make informed decisions about data tools and personnel. By having an idea of the cost of data debt, teams can more easily calculate their return on investment for a data discovery tool and get buy-in for budgeting purposes.

A whole new level of data discovery

Secoda makes data discovery a breeze with simple integrations, search and documentation that makes sharing your data knowledge a piece of cake.

Search for any data question at the speed of thought

Secoda allows anyone to answer any questions about your data without relying on your data team.

We the future of data discovery, just like the future of search, will be driven by large language models that allow anyone to ask any question to their data. Our mission has always been to give everyone the confidence to use data - this includes both technical and non-technical business teams.

Find the most trusted resources without relying on your data team

The potential is endless and we’re so excited to be part of the movement that is shaping the future of how companies find, use, and consume data.

Figure out where to go to find revenue, what tables have been transformed in dbt, what are tables with the least amount of documentation, and which tables you can trust with no PII.

Find any data asset with a Google Search for company data

Data can be scary. With Secoda , any teammate can start finding data and asking what what datasets mean and how to use them in their own day to day.

Our goal has always been to give everyone the confidence to use data and with Secoda's, every employee can have access to data wherever they work.