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Rapid AnalytiX Framework

Learning is the Essence of Organizational Agility

The pace of change is accelerating. Data is getting bigger. Networks are getting denser. Information abounds. But to use it advantageously, you must learn how to make it fit your organizational needs. And you need to do it quickly.

What is Excella’s Rapid AnalytiX Framework?

Excella’s Rapid AnalytiX Framework is a powerful tool that enables quick and lasting success with AI and Data projects. Rapid AnalytiX captures our extensive experience using Agile principles and practices and Lean Startup techniques to deliver AI solutions. It’s a new way of using these concepts to accelerate learning and harness the power of your data to improve your organization’s performance. 

With Rapid AnalytiX, we work with you and your stakeholders to clearly define the opportunity. We use our rich expertise to examine the potential of your data and explore multiple options in parallel. As we develop potential solutions, we collaboratively assess them using a design canvas and identify the most promising ones. We build those solutions using an automated MLOps infrastructure that allows quick comparisons and validation of the most effective approaches. Once they’re proven, we automatically deploy them into production and monitor their performance to ensure they give you lasting benefit.

Throughout this process, we use our AI Ethics Guidelines to ensure our solutions deliver responsible and ethical outcomes. We review the intended use case, the potential impact on individual and community welfare, and possibilities of bias. When we build our solutions, we ensure they are explainable, transparent, and trustworthy by taking a proactive approach to data, training, monitoring, and privacy. We build in controls to maintain “human in the loop” safeguards for appropriate oversight.

What Benefits does Rapid AnalytiX Offer?

Rapid AnalytiX is a revolutionary approach to delivering AI solutions. It improves the efficiency of AI solution development efforts by coupling the best principles of Agile with the best techniques of data science. In addition, it delivers several specific benefits that improve your organization’s ability to identify opportunities for AI and deliver solutions that meet them.

By deliberately framing the challenge, we bring focus to the “right” problem before building a solution and maximize the value of your investment.

By defining success criteria before developing a solution, we make it easier to pivot to more promising alternatives and accelerate the delivery of value.

By using a design canvas, we enable a systematic comparison of solution options and design alternatives and select the best for you.

By using our “zero baseline” approach, we get quantitative feedback on each model iteration and determine whether to persevere or pivot.

By coupling two loops together, we allow for iterative (Iteration) and incremental (New Functions and New Data Release) improvement of your AI solutions.

By using MLOps, we automate processes for training, evaluating, and deploying AI solutions and ultimately accelerate their development.

By using MLOps, we ensure the health of AI solutions by monitoring their performance and triggering automatic retraining when drift or other undesirable outcomes are detected.

By employing our AI Ethics Guidelines, we deliver AI solutions with responsible and ethical outcomes that are explainable, transparent, and trustworthy. We’ve written more about the importance of Explainable AI (XAI).

How does Rapid AnalytiX Work?

Rapid AnalytiX solves the problem of getting Agile and Data to work together, enhancing the effectiveness of both. Rapid AnalytiX is a powerful combination of Agile Delivery methods and Lean Startup techniques. It integrates the best features of both into a series of learning loops. These loops rapidly explore alternatives to identify the best opportunities and capitalize on them, so we use Agile’s emphasis on iteration and learning to enhance the research and analysis of data science. That allows us to quickly deliver solutions that balance desirability, feasibility, and viability.

1. Ideate:

In this optional stage, we work with your stakeholders to identify your most pressing needs and the best solution concepts for addressing them.

2. Explore:

Once we have identified a promising opportunity, we explore your environment, your data sources, and your infrastructure to develop the best solution alternatives.

3. Solution:

We capture the most promising solution ideas, including their ethical implications, on design canvases. In collaboration with you, we prioritize them and decide what to build.

4. Build:

We build the best solution approaches in parallel, using time bounded iterations and automated MLOps infrastructure to accelerate progress.

5. Validate:

At the end of each iteration, we assess what was built and determine whether to continue improving the solution, pivot to an alternative, or move to production.

6. Deploy:

When a solution approach is proven, we use automated MLOps infrastructure to deploy it to production.

7. Monitoring:

With MLOps infrastructure we proactively monitor the performance of production models and ensure they continue to deliver the desired results.

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Learn How to Harmonize Agile and Data Approaches to Achieve Your Business Goals

Download Rapid AnalytiX Factsheet

Contact Our Experts

Contact us to learn more about how Rapid AnalytiX can help you identify and solve your most pressing AI and Data needs.

Christina Seiden
VP, Strategic Growth
Claire Walsh
VP, Engineering and Services
Mathias Eifert
Managing Consultant and Technical Fellow