How to Identify High Impact Data Projects

Building a successful data strategy comes down to creating value for the organization. The best way to create value is to exclude projects that will waste resources, and prioritize projects with high impact.

What are your biggest challenges?

This is the time to be the explorer. It’s an opportunity to better understand your company, colleagues or employees. It’s important to have as many open and honest conversations as possible to find out exactly what challenges they experience.

Which aspects of their job are difficult? Are there tasks that are time-consuming but add little value? Or are there business processes that are prohibitively expensive?

• How do these challenges prevent them from hitting departmental targets?

• How do these challenges affect the company as a whole?

• What makes these challenges so problematic?

• What are the consequences of not solving the problem?

• How much money is the company losing because of them?

How does the solution benefit the company?

Once you have identified big challenges within your organization, you need to understand how solving each challenge will benefit the company.

If the problems were gone, what would the company’s improved state look like? Through conversations with your colleagues, you can explore how their department would benefit from the solution. Would automation save time or can something be done to reduce the cost of an expensive business process?

During these conversations, it is extremely important to understand exactly how they would like the solution to help them:

• What does their ideal solution look like?

• What elements of the problem are the most important?

• How would they measure the solution’s success?

Finally, you want to know exactly how this solution affects the company financially. Calculate how much money the company would gain by implementing the solution:

• Revenue increases due to improved customer acquisition

• Time saving resulting in reduced salary costs

• Cross-selling of products resulting in higher profit per customer

How risky is the project?

All investments carry risk, and data projects are no different. Therefore, it is important to understand what a project needs and the value it could create before you make the decision to invest in it.

Time-consuming projects are riskier for a multitude of reasons: they are more expensive, often need more effort and require input from more stakeholders.

Technical requirements and data availability also make the project riskier because you may need a specific set of skills to build the solution. Sometimes, a large amount of research needs to go into building a solution. These aspects make the project riskier because they make the outcome more uncertain or, make achieving the outcome more expensive.

Here are some costs to take into account when calculating ROI:

• Hourly rates for the employees working on the solution

• Time required to build and deploy the solution

• Infrastructure and hardware costs

• Monthly or quarterly costs to maintain the solution

Impact-effort matrix

Conclusion

Investing in the right data projects comes down to minimizing the risk of all data projects. Some projects are just too risky because the problem isn’t big enough or the solution is too expensive.

At the end of the day, the most important thing to do is to understand the problems, their potential solutions and how they add value to the organization.