Why are Businesses Challenged by Analytics?

By now, most of us have realized the importance of implementing data analytics in our businesses. However, we also know that not all the data we are able to gather are being utilized to its maximum capacity. So, why are organizations unable to utilize data? What are data analytics challenges that most companies face?

We have come up with the Top 5:

  1. Collecting Meaningful Data. There’s so much data for every aspect of business, and most of the time the employees get overwhelmed by the amount of data they have, making it difficult for them to decipher the critical insights. And they end up analyzing data that is readily available and not the one that truly adds value to the business. The solution to this problem – data literacy. Which means, as a company, you need to invest in training programs for your employees.
  2. Selecting the Right Tool. The second most common challenge is choosing from the numerous tools available in the market. It is best to seek professional help when it comes to determining which tool fits your needs the most. This will save you time, money, and effort in inappropriate tools.

  3. Consolidate data from multiple sources. Data comes from scattered and disjointed sources. For example, you will need to pull data from your website, social media pages, CRM portals, financial reports, emails, competitor’s websites, etc. The data formats will obviously vary. Combining and analyzing them in one place is one of the common challenges in data analytics. This is where organizations should focus on creating a centralized data hub. It will make it easier for employees to access information, and lessen chances of error.

  4. Quality of Data Collected. It is essential that the data you collect is reliable and accurate. One of the primary reasons behind inaccurate data is errors made during data entry. Another reason for poor quality data is the disparity in data. Suppose your data operator makes changes in one system and forgets to make the exact change in others; it will create asymmetric data.

    The first thing you must do is to automate the process of data collection. As for the challenge of asymmetric data, it is best to do a system integration.

  5. Building a data culture among employees. Most of the time, the company is ready to take on the new norm and keep up with technology. It is ready to do away with papers, folders, filing cabinets, etc. But, the challenge comes from the organization’s culture, and not its technology. The importance of data analysis needs to be extended to all your employees. Training and development should not be limited to the top-level executives, but also to the rank and file. You need to create a culture that understands data and supports it.

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