3 Phases of a Thorough Analytics Evaluation

insightsoftware -
March 31, 2020

insightsoftware is a global provider of reporting, analytics, and performance management solutions, empowering organizations to unlock business data and transform the way finance and data teams operate.

22 09 Blog 3phasesofathoroughanalyticsevaluation Web

What separates successful embedded analytics projects from failed ones? It often comes down to the evaluation process. Every application team starts by looking for the basics to enhance their software: charts, reports, and dashboards. Many stop there.

But if you need the analytics in your application to do more—drive revenue, increase customer satisfaction, differentiate your software—then you have to go further. Take the time to do a structured technical evaluation of analytics solutions to ensure they can meet your requirements.

A structured evaluation is more thorough than a trial or standard proof of concept because it includes criteria you have now and criteria you may not even be considering. It enables you to test technical requirements in your own environment, evaluate the vendor’s approach to your success, and familiarize your developers with the platform.

Here’s what you should expect during each phase of a structured analytics evaluation:

Phase 1: Define Requirements

In this first phase, you’ll define your requirements and develop an evaluation plan. This should be a joint evaluation plan with assignments to both your development team and vendor.

Review the plan and requirements with your vendor. Make sure they understand your business objectives and clearly communicate the expectations and milestones for each phase. Finally, review training and onboarding materials to get your team oriented before beginning development.

Phase 2: Set Up Environment

The goal of the second phase is to install software, connect to your data, and build the analytics. First, verify your team is working through the vendor’s training materials. Establish communications channels with the vendor—Slack, for example—as well as service level agreements (SLAs) on responsiveness.

Hold a conference call to install software in your environment. Next, have your team build out visualizations with the vendor and begin the knowledge transfer. Make sure to schedule regular check-in calls to offer support and keep the evaluation on schedule.

Phase 3: Test Requirements

In the final phase, you’ll prove out all requirements and build a partnership with your chosen vendor. You’ll likely hold several check-in calls to work through any final questions, get best practices, and verify the evaluation requirements are still valid.

By the end of this phase, you should be able to demonstrate proof points that the analytics solution has met the technical requirements. What’s more, you should feel confident you have the analytics support team you need to get into production—and stay in production— successfully with your vendor. At the same time, your developers should feel like they have a partner, not just a vendor—someone who is committed to their short- and long-term success.

To learn more about choosing an analytics vendor, read our BI Buyer’s Guide

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