Every organization generates a large volume of data from multiple sources and it has changed the way business is done. Businesses know they need to dig into their data to unlock the efficiency and improved services buried in that information. The value of applying data to operations and business processes has resulted in competitive advantages and changed the industries entirely.

Traditionally, businesses used Excel spreadsheets and other similar tools to compile raw data, which was then analyzed manually. This was both tedious and time-consuming. Also, the company needed to make significant investments in data analysis and the results were not accurate.

Thus, unlocking the value in data isn’t easy. The availability of more information and the technologies that store, manage, and analyze it, has resulted in multiple choices for the CXOs to choose from to support their Analytics requirements. This puts them in a dilemma to select the right option considering their key challenges like available budget, availability of skilled resources, long-duration analytics implementation project, etc.

There is a remedy for companies, however, with Analytics-as-a-Service emerging as a viable option for any organization that needs Analytics without the capital investment to handle the above challenges.

The following 10 signs show “Analytics as a Service” is a valuable proposition for your organization.

  1. Your staff spending hours compiling information from multiple systems
  2. You want to improve the success rate of product and service across location and units through “single source of truth”
  3. You don’t have KPIs to measure overall success
  4. it’s hard to trust the accuracy of reports built-in spreadsheets
  5. Your data comes to you in email form
  6. Opportunities are not converting as well as you like
  7. Profit Margins are not as per your expectations
  8. Waiting on data reports from your IT causes a bottleneck or loss of opportunity
  9. Your department data exists in silos and collaboration is hard
  10. Your decision making is driven by gut feel rather than data-based actionable insights