Data Discovery & Automation Insights

4 simple steps to a successful data project

Written by Danilo Drobac | May 28, 2019 6:02:00 PM

With the rise of interest in data and its business applications, everybody is embarking on their own journeys to uncover value. Unfortunately, not all of them are successful.

To run a successful data project, we recommend breaking the process down into 4 simple steps.

Follow these 4 simple steps for a successful data project

1. Start with value

Make sure you know EXACTLY what you're trying to achieve and how you'll measure it. This might sound obvious, but it's why most data projects fail before they've even begun.

Have you assessed your business and found a real pain point that you're looking to fix or are you running on a hunch? Until you have true value (in £ form or other), anything you run with will simply be a nice-to-have and therefore will not resonate with the leadership team. Getting this right also means you've already set up your goalposts of how you'll measure success.

2. Ensure the goals of your key stakeholders are aligned

It's not uncommon for different stakeholders to have different expectations on the output of a project so that it supports their agenda. This does not translate to value for the entire business and therefore makes success more challenging. Have everybody agree on the strategy early on so that you know you're heading in the right direction.

3. Keep things simple

There's a stigma around data. Some feel it's too complicated and hard to get started. This comes from thinking too big from the outset and providing complex solutions for edge cases and problems that might occur in 12-24 months.

Whilst it's always good to think long term when you're providing a solution, start small and iterate. Break the problem down into multiple iterations so it's easier to articulate and deliver results continuously. 

This method provides a constant feedback loop that can help steer the rest of the project.

4. Let the projects evolve organically

There's often some degree of bias at the outset of a data project. Even from the initial data discovery workshop, many are guilty of having a pre-determined notion of the direction they want a project to follow. For example, they might prefer a specific tool or solution that might not align with the primary focus or add value.

By iterating on a project, you have consistent feedback to work with. You'll know your efforts were successful when you start getting new and exciting questions from people as you expand their horizons with what's possible.

Use this to fuel the next initiative. Is it an extension of what you've already delivered so far? Or a completely new idea that has its own value and requirements for a new project? This is the key to evolving in the right direction, by tackling the challenges that will make a difference in your business.

Data projects don't have to be daunting

It really can be as simple as that. Our entire philosophy is to provide value from data in an accessible way. And we do this by following these 4 steps:

  1. Tackle a real business challenge. Be clear on the associated value and success measures
  2. Get all of your stakeholders to agree, as early as possible, on your project goals
  3. Keep things simple and iterate over time
  4. Let your results spark interest and define the evolution of your projects

We believe so strongly in being able to simplify your data projects, that we've built an entire methodology that can take you from any stage of your digital transformation to a place where you can reap the rewards.