Challenges to Thriving in the Digital Data Explosion

The McKinsey study shows it’s mainly a function of not being able to scale analytics, so firms only use a slice of the business to apply big data or only do so on a test basis. It’s like they’re afraid to gamble on big data — and forgoing 59% of the return they could experience with effective analytics.

In their study, here are the reasons firms aren’t getting great ROI from analytics:

Managers prefer data mining for diamonds rather than engaging in a sustained, scientific data analysis effort.
Front-line managers fail to understand analytics, seeing results as “black box” tools that don’t generate faith in the findings. Hence, insights don’t translate into improved decision-making.
Legacy systems within the firm actually impede use of analytics insights. It’s not an accident that companies like Amazon, which were formed around big data, thrive in the digital data explosion while their competitors simply drown.

Data-driven firms have pushed decision-making Payroll Directors Email Lists down in their relatively flat organizations, while their competitors flail about awaiting approval from bloated organizational hierarchies.
digital data explosion
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First, firms need to hire skilled analysts

to manage digital data. Only 18% of companies believe they have the skills to effectively analyze data. Unfortunately, there’s a serious shortage of trained BI (business intelligence) employees. And, in many cases, the few folks with the skill set to perform analytics are out of computer science and lack the understanding of business processes necessary to drive decision-making based on analytics and business schools have fallen short in adopting BI training in their curricula.

And, the salaries offered don’t match the skill set required. Hence, firms end up hiring folks inadequately trained in analytics with far too little practical experience to provide necessary insights.

Solution: hire or train those with business process understanding to manage data analytics

Secondly, organizational structure impedes use of analytics to drive decision-making.

Solution: Empower front-line employees to make decisions based on real-time data. Management experts argued for decades that flatter organizations were needed. Data analytics makes this imperative.

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