Enterprise Analytics 104: Insights To Action!

Nexdigm USA

Contributor

Nexdigm USA
Is the buzz around analytics dwindling? Once hyped as the gamechanger for every enterprise, is analytics letting businesses down now?
United States Corporate/Commercial Law
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Is the buzz around analytics dwindling? Once hyped as the gamechanger for every enterprise, is analytics letting businesses down now? While investments in analytics are at an all-time high, impact, i.e., improvements resulting in an increase in revenue or decrease in costs, is still low. According to a Deloitte survey, 47% of organizations reported little or no improvement in their competitive positioning from analytics initiatives. The question that remains then is that when data and technology made the boom of analytics look so promising, where did things go wrong? The answer lies in the way analytics is being adopted in the current business scenario. Impact at a scale needs implementation at that scale, and that is what is missing in the big picture of data. Limited adoption and integration have been cited as the biggest reason for the failure of analytics initiatives. While 81% of companies agree that data should be at the heart of all decision-making, only 31% have significantly restructured their operations to help do this. (Source: EY)

To understand where we are lagging, it is important to look at challenges that restrict ingrained analytics within organizations.

Culture Shift In Data, We Trust.

Historically, businesses have been known to be governed by gut and intuition much more dominantly than data and rigor. This was primarily because data was either sparse or not available, and executives used wit and intuition along with years of learning and experience to uncover patterns from data. This old school approach of HIPPO – the highest-paid person's opinion needs to now be re-shaped. We have to move to asking the right questions from data instead of giving the right answers, intuitively. While such a seismic shift might not be possible all at once, augmenting and validating intuition with analytics and moving away from reliance on gut and thumb-rules is crucial if analytics has to yield tangible results.

Decoding the Ones and Zeros Fifty Shades of Grey.

Another major challenge in frontline adoption of analytics finds its roots in the lack of trust and confidence in analytics. Although there are FAMGA stalwarts from Silicon Valley advocating a strong case for a digital and data-centric approach to every aspect of the business, data culture defines the very backbone and core IP of these tech-savvy businesses. This isn't true for many conventional businesses though, for whom success in analytics has been narrow and limited only to a few beta tests or small slices of business. Analytics is still being conceived as a 'black box' by business decision-makers and they don't have a behind-the-scenes understanding of it. Some of this skepticism can be attributed to complex analytical models and the rest to lack of skills in business individuals to interpret analytics. Driving change management by upskilling resources and making specific attempts to tie decision cultures and processes with data can help analytics initiatives gain traction across the enterprise.

Operationalizing Analytics Lost in Translation.

Many times, the ownership of implementation is not very clear between analytics, IT, and business units, and this can lead to limited tangible results from the initial promising pilots. Often, what can be easily analyzed might not be so easy to implement and vice-versa. Operations are not as dynamic as analytics; hence, it becomes essential to capture quick wins, build-on the initial momentum, and trust gains to implement advanced analytics solutions. Projects with the highest visibility, highest business value, and lowest execution complexity can be a good place to start and understand the impact analytics can generate.

Understanding the above-stated execution challenges has become extremely important as organizations take small steps towards data-driven decision making. An external expert can support businesses in this transition through a sturdy foundation of industry best practices and frameworks to handhold, train, and educate stakeholders in this journey of deriving value from data.

This article is the fifth in a series of six, where we discuss some of the most commonly faced obstacles in the adoption of analytics.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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