Why do analytics initiatives fail?


analytics initiatives

Businesses have a plethora of options when choosing an analytics strategy - from choosing products and architectures to selecting service partners and deciding upon implementation methodologies. While technology choices play a major role in the success of an analytics initiative, a little careful research can point one in the right direction. Almost all of the industry leading data integration, analytics and BI products have proven capabilities that can get the job done.

Despite this, a 2015 report from Price Waterhouse Coopers and Iron Mountain shows an alarming failure rate of analytics initiatives. They surveyed 1,800 senior business leaders in North America and Europe at mid-sized companies with more than 250 employees and enterprise-level organizations with over 2,500 employees. According to the study, 43 percent of companies surveyed "obtain little tangible benefit from their information," while 23 percent "derive no benefit whatsoever."

So, why are so many analytics initiatives failing? We believe one of the reasons is an organizational disconnect between information and intuition. Let’s explain what we mean.

Data analytics provides information, or insight, which is an essential component of decision making. However, this is only one component of a good decision. It is incomplete, and potentially misleading, without intuition - its complementary partner in any sound decision making process. Intuition stems from expertise, or wisdom gained through practical experience, and manifests in an entirely different way than analysis. By nature, intuition is uninvited, instantaneous and generally considered to be unpredictable. For this reason, businesses have mostly steered away from actively integrating this ubiquitous human capacity into structured decision making processes.

Intuition provides vital capabilities such as recognizing patterns, making holistic associations, and providing hypotheses for action. If properly utilized, intuition is a perfect complement to information gleaned from analytics pipelines. Most organizations lack a defined mechanism to optimize the integration between information and intuition, hence they fall back upon habitual patterns, or muscle memory, that lean too heavily upon one or the other. By learning how to fine tune this balance through carefully designed measurement and sensing structures, organizations can leap ahead of competition, fuel growth of revenue and profits, foster innovation and improve their culture.

Data Intuition methodology

The Data Intuition methodology from DataIn2it guides an organization towards this balance of information and intuition through a series of facilitated workshops. Leaders are given a framework to define a business problem, identify its components, determine what should be measured and what should be sensed, learn how the measurement and sensing structures operate, and discover how to integrate these into a collaborative decision making process. With this framework, an analytics initiative is calibrated to deliver better data, resulting in improved collaboration, helping teams to make smarter decisions and driving exceptional results.

Through the Data Intuition methodology, an organization is taken through a series of structured workshops over 4 months, which provides the process, tools and training for ongoing utilization of the methodology, and an actual end-to-end execution of a single business problem. The methodology is product agnostic and can be applied in any analytics environment.

Contact us today to learn more.


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