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3 Low Cost and High Impact Initiatives in Analytics for Every Organization


Value of Data

One of my favorite saying in the analytics world by Intel is "Data is the new oil, what oil did for the 20th century, data will do for the 21st century". Before oil can be used for productivity (like for gas in vehicles), it needs to be extracted, mined, and refined through a long pipeline of value-add activities. Data is like oil, it needs to be extracted from databases, mined for information (data manipulation, cleaning, ETL), and it needs to be refined (ML prediction, statistical analysis). Unliked oil, you can create the data resources that will be of value to you, so long as you are willing to put in the investment to collect these data points.

The Problem

As an analytics services company, we have talked to hundreds of organization (private, non-profit, government, large or small), and one of the biggest challenge is the lack of understanding to what analytics they should be doing as they lack the context and expertise. As the saying goes, you don't know what you don't know. I hope this short blog can give you some ideas on how to get started by outlining three low cost and high impact initiatives in analytics for every organization to get started on.

1) Data Strategy

Do you have a data strategy? Very often a potential client will call us inquiring about our services and doesn't have any idea how analytics would apply to their data. In those cases, we start with an assessment of the organization's strategy, data and capabilities and build a plan strategy around data. It doesn't need to be a complicated or expensive exercise. The primary goal is to ensure that your data strategy is aligned with your current and future business/organization strategy.

Some questions to kick it off:

  • Data Collection

  • What data is being collected? How frequently is it being collected?

  • Data Usage

  • What variables are being used on a regular basis for decision making? Who is using it and how often?

  • Which data points are core to your business?

  • Think through how data is collected at various functions in your organization (finance, marketing, HR, operations).

  • Future-proofing

  • What data should you start collecting now because it can give you useful information in the future?

Ultimately, you would want to have a solid 5 Year Data Strategy that is in line with your organizational strategy and potentially a Data Governance Document as well as a Data Analysis Framework.

2) Data Analytics Education

One of the cheapest way to level up your organization's data skills is to give the tools and knowledge into the hands of your staff. Data analysis tools has become so widespread and easy to use that it doesn't take too long to learn them. In the Data Science workshops AAARL runs, we teach staff how to build and use data dashboards in under 3 hours. We teach people who have never coded before how to use R to build statistical model for analysis in four hours and teach basics in Machine learning in four hours. The possibility is limitless once your team has the foundation to explore deeper into your data. You will find trends and levers to change outcome that you never known before!

3) Dashboards

In the perfect world, you wake up and have accurate information on what decisions to make. You will know how many customers will come to your door, what the weather will be like, or where the inventory level is at. In the real world, you often get these information either too late or just don't get them at all. If you have the data collected, you can easily put them into a user friendly dashboard and just refresh the data when you want to update it. The top three widely used vendor for dashboards are Qlik, Power BI and Tableau. Qlik and PowerBI has free personal use versions and it's very powerful for anyone to get started on.

Final words

As with any other skills in an organization, there are ways for you to level up. It's a journey that effects every part of your organization and in a digital world, is core to the success and survival in our industry.

#analytics #strategy #data

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