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3 Analytics Tools for Your Team and 3 Selection Advice Considerations


Whether you work in risk, marketing, procurement, audit, IT or any other area - there are 3 types of data/analytics software that your team should have access to, at a minimum.


Of course, there's a lot more to analytics than just software / tools.

(e.g. objectives, hypotheses, process understanding, etc).


But tools enable the outcome.


The minimum set of analytics tools for your team:


1. Data Cleansing:

  • Data is rarely clean or in the format that you need for your analysis.

  • There are newer automated tools - leveraging AI to help with the cleansing.

  • There are open source options; for basic needs, there are Excel Add-ins like ASAP Utilities.


2. Data Analysis (can be the same tool as the one used for cleansing):

  • You can still write code, if you really need to. But do you want to invest in that?

  • Point and click options (workflows, rather than code) are becoming quite popular.

  • There are open source options for both the workflow style tools and for coding.


3. Data Visualisation (some also handle cleansing and analysis):

  • To better understand, explore, interact with and present results.

  • There are quite a few mature tools available.

  • There are open source options, but mostly with high learning curves (for now).


If you are considering external advice


You may look for advice regarding tool selection. If you do this, make sure to check:


1. Does this align with my corporate technology stack / architecture / existing licensing?

  • Don't upset the tech team. You want to do the right thing, and not lose your tech support.

  • There is no point in buying if you already have licenses for a good alternative.

  • It can be difficult to implement a tool if it does not fit into the existing architecture.


2. Have you been given all the information you need to evaluate the recommendation?

  • We recently saw a report that recommended two tools.

  • For the visualisation tool, an analyst's magic quadrant was included. The high ranking tools were considered in the report and the recommended tool was one that was rated highly.

  • For the analysis tool, the magic quadrant was not included. The high ranking tools were not considered in the report and the recommended tool was not rated highly. The recommended software vendor provides good commission rates to their partners. Enough said.

3. Will your team use the tools?

  • Does the capability exist or can it be acquired reasonably easily?

  • Does the team want to use that tool - if they're objecting, is the objection reasonable?

  • Is the tool too simple or too advanced for the intended use cases?


As a leader, how are you equipping your team to use your data to better serve your customers?


This article is part of the assurance analytics series.


Go to the Assurance Analytics Guide

Fin Services Public Sector Assurance / Audit Analytics