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Your Big Data Can Send Your Performance Skyrocketing   Featured

Your Big Data Can Send Your Performance Skyrocketing    Ivan Diaz

Every organization today is thinking of how it can get maximum value from the information it gathers from daily transactions. With the new technologies emerging leading to a massive collection of data more than ever, many organizations are struggling to find ways to obtain value from data and compete appropriately in a fast-paced marketplace. However, they keep asking themselves how best to achieve value. Knowing what happened and why it happened is no longer enough. Rather, organizations must know what is taking place now, what might happen in the future, and what actions should be taken to get the best results.

According to a study done by MIT Sloan Management Review, the source of pressure for many organizations is innovating to achieve a competitive edge. This was cited by 6 out of 10 respondents. Similarly, the same number of people stated that their organizations have more data than they can use effectively. Most organizations leaders want to use analytics to take advantage of growing data. They also need computational power to get smart and innovative in ways they could never have managed before. With proper simulations and scenarios, the smart and innovative approach to data can provide the best actions and guidance that can be taken when disruptions occur from unexpected events like earthquakes and floods, among others. Executives are interested in knowing the optimal solutions based on complex business parameters or new information, and they want to take action quickly.

The same study found a clear connection between performance and the competitive value of analytics. Based on the data from respondents, they agreed that organizations that agreed that the use of business information and analytics differentiates them in their respective industries were twice as likely to be top performers. Compared to their peers, the top performers approached their business operations differently. For example, they use analytics in most of their decision-making activities. Furthermore, top performers were twice as likely to use analytics to guide their future strategies and day-to-day operations. Accordingly, they make decisions based on rigorous data analysis compared to the lower performers.

Organizations that understand their current position with the adoption of analytics are better prepared to turn their challenges into opportunities. These organizations were ranked as Aspirational, Experienced and Transformed, where each one had clear distinctions.

Aspirational organizations are far from achieving their desired analytical goals. They often focus on the efficiency or automation of the existing processes and search for ways to cut costs. Aspirational organizations have fewer building blocks like people, processes, and tools currently to gather, understand, and incorporate or act on their insights.

Professional organizations are the ones that look into going beyond management after they have gained analytics experience at the Aspirational phase. Experienced organizations develop better approaches to collect, incorporate and act on analytics effectively so that they can start optimizing their organizations. On the other hand, transformed organizations are those that have great experience in using analytics for various functions. They use it as a competitive differentiator and are good at organizing the people, tools and processes to the optimum. They are not focused much on cutting costs like the aspirational or experienced organizations. Rather, they concentrate on automating their operations through the effective use of insights.

Although there is a notion that getting your data strategy right is hard, it is not a big challenge that organizations face when adopting analytics. Based on the same study, only a few of the respondents cited challenges with the quality of data or ineffective governance of data as the biggest obstacle to their big data strategy. Instead, it emerged that the biggest obstacles that organizations face are associated with managerial and cultural issues related to big data and technology.

 

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

scottkoegler.me/

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