It's often assumed that the more sophisticated analytics become, the higher the skills needed to achieve them. We don't think so.
Not long ago I attended a Gartner webinar focused on how Business Intelligence has become a core competency in organizations worldwide. One of the main frameworks the presenter showed was related to how the use of BI represents an evolution process that according to them, has four stages:
1. Descriptive Analytics - What happened?
2. Diagnostic Analytics - Why did it happen?
3. Predictive Analytics - What will happen?
4. Prescriptive Analytics - What should happen?
In their framework, Gartner makes the assumption that the more sophisticated the analytics become, the higher the skills needed to achieve them. This made me think about this 2011 report from IDC that stated that data will grow by a factor of 50 by 2020, but IT professionals will only grow by a factor of 1.5. Which leads me to wonder: Is it really possible for most companies out there to embrace prescriptive analytics and become fully data-driven organizations?
Interestingly, we at TARGIT have been working on a framework to describe a similar evolution in BI adoption. We call it the TARGIT Journey and if you're a regular reader here on the TARGIT blog, you've definitely seen it before:
We don't include the axis of increasing required skills though. Why? Self-service analytics.
Halfway through the webinar, the host asked us (200+ attendants) to vote on the following question: Does your BI program manager report only to an IT director or to a business function? Or better said: Are your BI capabilities being handled centralized to the IT department or truly embraced throughout the organization?
The results were interesting, with 30 percent of attendees stating that their BI program manager had reporting lines with other departments. However, over 50 percent said that their BI program manager reported only internally within IT. Last year, that number was 85 percent. Clearly, business functions are realizing the value behind self-service analytics and are demanding Business Intelligence ownership. They are decentralizing those capabilities and making them available to everyone.
Next, the host asked us to point out if our Business Intelligence implementation and support came from an IT budget or a business budget. With an even 50-50, half of companies considered that all their departments paid for those capabilities, and the other half considered it an IT budgeted investment.
Considering these results, it's clear how departments such as Marketing, Sales, Finance, HR, etc. feel that they have been paying for something they are not receiving. They want to become data-driven roles. However, with a centralized Business Intelligence practice, there's a common frustration throughout different departments, as they are forced to create their own diagnostic, predictive, and prescriptive analytics tools. This generates unnecessary spending. It's not only a waste of time, but also resources of people tasked to keep those unique tools updated and accurate. The ROI of BI is nonexistent at this point.
Self-service analytics are the only way to keep up with the data growth. The only way to make sure that companies will be able to handle the exponential data growth that analysts and research agencies predict will come is by embracing Business Intelligence and data discovery tools as a decentralized organization. This will enable anyone in the organization to make fact-based decisions without the need to rely on the IT department. It's a world of efficient decision making, ultimately boosting the ROI behind the BI investment.
Prescriptive analytics should be a walk in the park, but you need self-service analytics first.
Want to learn more about the journey to becoming a truly data-driven organization through self-service analytics? Download the free eBook "3 Steps to Becoming an Analytics-Driven Organization" or check out the free on-demand webinar from TARGIT CTO Dr. Morten Middelfart "The Journey to become an analytics-driven company."
Lead Generation Manager at Carbonite
An Industrial Engineer with a passion for Marketing. I enjoy understanding manufacturing and supply chain processes and ways of improving them through better data mining and analysis, ultimately finding those insights that could take businesses to the next level. I have extensive experience with TARGIT Decision Suite, and a passion for a data-driven way of life...