Introduction
In the current AI revolution, businesses vet hundreds or even thousands of potential use cases for automation.
With limited resources and increased competition, businesses need to be sure they’re prioritizing the right use cases. Evalueserve’s CRUISE Framework helps organizations do just that.
The 2×2 Matrix, also known as a magic quadrant or four blocker, is another framework often used to prioritize analytics use cases, but we find it inadequate for a few reasons.
Meet Swapnil Srivastava, who explains why businesses need a tried-and-true method for prioritizing analytics use cases.
What I have seen and observed is that the majority of organizations follow the consultants’ favorite – a 2x2 Matrix approach. In this approach, they will use metrics like cost or feasibility, or impact, and categorize them as low, medium, or high on the XY plane. Where these use cases land on that XY plane dictates their priority…
This approach is incomplete and also has some major flaws.
Swapnil shares real business examples of why two-by-two matrices are insufficient for prioritizing use cases.
CRUISE provides a better analysis of use cases for an enterprise that wants to weigh context in its short- and long-term strategies.
CRUISE Framework:
What It Stands For
All of these are factors that organizations should consider when prioritizing analytics use cases. Below, we’ll dive into each factor, why it’s important, and how it impacts prioritization.
Learn from the expert: Swapnil explains the first three parts of the CRUISE Framework.
Complexity of Project
To determine the complexity of the project, you’ll consider factors such as:
- The analytics maturity level required
- i.e., descriptive or predictive
- The duration of the project. Usually, the more complex the project, the longer it will last, by default.
- The algorithmic complexity involved
- The type of technology
- The number of stakeholders
- The number of geographies or time zones
Higher complexity can mean a higher or lower score for the use case, depending on what the organization is looking for.
ROI of Project
Before starting a project, you’ll want to estimate its potential ROI. The higher the estimated ROI of a use case, the higher its score with the CRUISE Framework.
Different types of ROI that are considered include:
- Revenue impact
- Expense impact
- Market share
- Profitability
- Automation-driven productivity gains
- Asset utilization
- Customer Satisfaction Score (CSAT)
- Employee engagement
Universality
The universality of a project speaks to how readily it could be repeated in other areas of the business. Could the algorithm be reused in a different department?
The more a use case can be replicated and reused, the higher its value to the enterprise, boosting its CRUISE score.
Swapnil rounds out the remaining components of the CRUISE Framework.
Integrity of Data
The next step in prioritizing use cases is to consider the following:
- Do we have the necessary, relevant data for this use case yet?
- If so, is that data high quality?
If the answer to both of those questions is yes, that use case receives a high score on Integrity of Data. A low score presents a potential issue with prioritization – in analytics, you can’t do anything well without a solid foundation of high-quality data.
Strategic Alignment
It will be incredibly hard to fund any use case that doesn’t align with your organization’s overall strategy and priorities. This alignment could be direct or indirect.
A use case that would improve employee engagement would score decently well in an organization wanting to capture market share. It’s indirectly aligned, because higher employee engagement should ultimately result in higher sales.
Ease of Implementation
When deciding which analytics use cases to implement, consider your resources. Do you have the proper tools, technology infrastructure, staff, and change management processes in place for the project?
If so, you’ll receive a high score for ease of implementation.
Every time you start a use case, you should make sure that you have the right data, the right technological infrastructure, and the right platform in place.
Swapnil discusses scoring your analytics use cases and gives a few final tips.
Conclusion
Now that you understand each individual factor of the CRUISE Framework and its importance, it’s time to give your analytics use cases overall scores.
You can use both rule-based and algorithmic techniques to score your use cases against the CRUISE Framework. The simplest way is to average the score of all the parameters.
Here are two final tips:
- There are usually analytics use cases that make sense to implement before others, as the first use case can pave the way for the second. Some projects are a prerequisite for others. It may be necessary to sequence your use cases.
- Refresh your analytics roadmap at least once or twice a year. Priorities shift, business environments change – it’s important to make sure your analytics work is still aligned.
