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PCSOFT has been serving the Smeaton Grange area since 2005, providing IT Support such as technical helpdesk support, computer support, and consulting to small and medium-sized businesses.

Interpreting Analytics Isn’t Always Cut and Dry

Interpreting Analytics Isn’t Always Cut and Dry

In business, making good decisions is a must. You have to manage risk well. Today’s business is using analytics to drive decision making, and therefore needs to design and implement platforms that make this possible. If a business doesn’t properly set up their analytics or intelligence systems, their decisions may not be made with a useful perspective. Let’s take a look at these systems to see if you may be being fooled by your own numbers.

Knowledge Base

You’ve been using analytics for your web traffic, and it has worked so well that you are looking to implement a system that will allow you to look at the numbers for your entire business. The first thing that any business has to realize is that they’ll need a reliable cache of information if they want to get any proper reports. To do that, there needs to be a database that properly represents the data you want to analyze.

The data warehouse is essentially a strategy where the databases that your organization uses to function are also stored in a massive central database that will allow the sophisticated analytics software to have the best representation of your business as possible. By feeding a centralized database from all outlying databases, you will have all the data you need to get a proper read on how your business is functioning.

Mistaken Conclusions

The other half of getting analytics to work for your company is the actual deciphering of the figures. This means reports...lots of reports. There are some seemingly simple mistakes people make when reading reports that lead to wasted capital and resources and inefficiency from bad suppositions. Here are a few examples:

  1. Correlation Doesn’t Always Mean Causation - There are times when you will be comparing seemingly similar metrics only to discover that the two variables have no direct (or indirect) relationship with each other. Make sure similar trends aren’t just coincidences before acting on your data.
  2. Make Sure to Keep Everything in Context - When you are actively using analytics and you start making headway in one facet of your business, it can be intoxicating. It’s best not to transfer a false optimism to other parts of your business. If the indicators say they won’t work, they likely won’t.
  3. Too Many Stats - Whether you are just tracking too many metrics, or you are tracking some that are completely meaningless (and therefore worthless), spending time on erroneous metrics can convolute your goal of understanding the practical operational effectiveness of your business. Scale your reports back to measuring metrics that you know are more meaningful.
  4. The “Wow” Factor - Metrics that report very positive or very negative situations will always be outliers. A good rule of thumb is to look into what’s causing this data to spike or drop like a rock.

Business is changing, and to get more, you need to use your data. If you would like some information about how to integrate data analytics into your business, call PCSOFT today at 02 98730080.

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Friday, November 22, 2024

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