Category: Analytics Survey

Survey Results: Devote More Time For Data Analysis

Most Analysts Spend 50% of Their Time Finding Data

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

Most analysts spend most of their time finding data.

Among other thing this can mean they are setting up data mining or data gathering process to look for the data or it can mean they reviewing their data for relevancy.

My experience is that when you spending this much time on the finding the right data phase it reflects a poorly structured data environment or a unfamiliarity with the data needed.

Dirty data is also a big time waste.

Experience is the best solution for challenges with finding data. The fact the finding phase % is so high speaks to both the explosion in the 3 V’s of Big Data (Velocity, Volume and Variety)  as well as the number of analytics newbies.

To me this should be no more than 20% of your time.

I expected finding data would be the biggest chunk, but was surprised that over 50% of my analyst connections using at least 40% of their time finding data.

If you have one day to answer a key business question, this means you are using your entire morning just finding the data.

When you get back from lunch you haven’t even started the actual analysis yet and the clock is ticking.

Data is based on a survey I sent to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

Quick Analytics Career Question

Greetings to You My Valued LinkedIn Connection,

I was talking with a young professional just getting started in his analytics career. During our conversation we discussed what is most important to being a great analyst. With that in mind, I’d ask you to share your thoughts.

In your opinion, of the following ways to learn about analytics, which one has been the most important in your career path?

  • Formal Education – A degree or certificate in an analytics related field.
  • Self-Learning – Using trial and error and online resources.
  • Subject Matter Experts – Being trained/mentored by an expert.
  • Seminars/Workshops – Attending events to acquire new knowledge.
  • Technical Training – Attend training on specific technical areas.

Thanks for sharing. As always I will roll up all the replies I get and blog about it.

Dan Meyer, Analytics Champion, http://www.dmaiph.com

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Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

Most Analysts Spend 50% of Their Time Finding Data

Most analysts spend most of their time finding data.

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

In fact, most analysts I know spend 50% of their time finding data.

Among other thing this can mean they are setting up data mining or data gathering process to look for the data or it can mean they reviewing their data for relevancy.

My experience is that when you spending this much time on the finding the right data phase it reflects a poorly structured data environment or a unfamiliarity with the data needed.

Dirty data is also a big time waste.

Experience is the best solution for challenges with finding data. The fact the finding phase % is so high speaks to both the explosion in the 3 V’s of Big Data (Velocity, Volume and Variety)  as well as the number of analytics newbies.

To me this should be no more than 20% of your time.

I expected finding data would be the biggest chunk, but was surprised that over 50% of my analyst connections using at least 40% of their time finding data.

If you have one day to answer a key business question, this means you are using your entire morning just finding the data.

When you get back from lunch you haven’t even started the actual analysis yet and the clock is ticking.

Data is based on a survey I sent to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

DMAIPH Quick Data Survey

A few months back I sent a quick survey to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Here is the question I asked.

Greetings!  I’m hoping you can help me gather some data for a book I’m working on. If you had to breakdown the work you do into 3 buckets; finding data, analyzing data and reporting data, what would the % of each be? A quick reply with your breakdown would be hugely helpful in my research. Thanks!   Dan Meyer, Analytics Champion, www.dmaiph.com

I got back over 400 replies.

Here is how they broke down.

 

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

The higher the %, the more each analyst spent time doing that particular phase of analytics.

Here are some of my takeaways from this simple (and very nonscientific survey)

  • I was surprised to see 45% spend half their time or more on finding data. To me this is one of the telling signs that Big Data has led to a shortage of top analytics talent.
  • Only 1 out of 4 analysts are spending 20% of less of their time finding data. These are generally senior analysts, well established in their company.
  • Only half of my analyst connections are spending 40% of more of their time on conducting analysis. With significant time spent on finding and/or reporting data you can imagine a lot of important discoveries are being missed and opportunities lost.
  • Only 1 out of 3 analysts are getting spend my recommended 50% or more of their time actually doing analysis work.
  • Based on my survey, reporting gets shortchanged a lot. All in, 96% of respondents spend 30% of their time of less on reporting.
  • My recommendation is that you spend about 30-40% of your time on the reporting aspect, and sadly only 4% of my analytics connections are able to do that.

In an ideal world, I would expect an analyst to spend no more the 30% of their time on finding data, and at least 30% on reporting their findings, leaving more or less 40% to do the actual analysis.

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This breakdown is based on my own experience as an analyst as well as seeing how analyst working for data-driven companies work.

Only about 30% of my 400+ analytics focused LinkedIn connections come close to meeting my recommended breakdowns.

Which means I have a lot of work to do.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.