Effective analysis repositions business value of data

Effective analysis repositions business value of data

If data is the oil of the digital age, then analytics is the electricity that delivers the current, giving the insights necessary to affect change. Just like oil, unrefined data is ‘dirty’ and needs to be understood and refined to deliver value. Therefore, to really leverage the power of the data at the organisation’s disposal, it needs to have an effective analysis approach and a great analytics environment in place. 

Such an environment enables decision-makers to unlock business value more innovatively than has been possible using traditional, legacy-focused solutions. Data is continuously growing and evolving as the needs of the organisation change thanks to shifting customer expectations. And when there is a Black Swan event such as the current COVID-19 pandemic, analysing data is crucial to deal with the problems faced by companies. With an effective analysis approach and better understanding new environments through data, organisations can greatly improve their chances of thriving during the difficult economic times of this dynamic new world. 

Now, more than ever, an effective analysis of data is crucial to business success. But it needs to be focused on understanding the unique challenges inherent to each organisation and how to overcome those while delivering the results required for a digital transformation journey. 

Analytics-driven strategy

HBR research following the 2007 financial crisis examined four responses to the slowdown that occurred and identified the best ways for companies to deal with a crisis and overcome it. It found that the optimum strategy combines offensive tactics, specifically market development and asset investment, with a defensive one of improving operational efficiency. And the golden thread tying everything together is analytics. 

From a market development perspective, the focus is on gaining customer and product insights. For its part, asset investment centres on ROI analysis and financial modelling to deliver operational efficiency requires both operational and inventory analytics. There is simply no getting around the need to refocus efforts on understanding data and all its complexities especially when it comes to these three pillars. 

According to the 2020 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms, essential components of modern analytical tools include natural language queries, digital storytelling, embedded analytics, and automated insights. And to further differentiate themselves in how they apply these innovations, companies need to integrate support for enterprise report capability with augmented analytics. 

Of course, a business intelligence (BI) tool cannot do this on its own. It must have a certain amount of intelligence to operate effectively inside the organisation. 

Analytical platform

Take Microsoft Power BI as an example. It was developed as part of an entire platform and not just a stand-alone tool. With a community of more than one million members who can vote for features to be shipped in the next release, it is the leading analytical environments available today. 

And by leveraging the local experience of partners such as Altron Karabina when combined with the functionality of Power BI, companies can radically transform their business and technology platforms. What makes Power BI such a compelling offering is its ability to integrate machine learning (ML) with artificial intelligence (AI). It understands natural language from the data set of a company and empowers users to train the model based on the terminology and concepts used inside the business. Each implementation, therefore, becomes an agile and growing analytical environment that adjusts to what the organisation requires and how it uses the platform. 

It delivers the vehicle for effectively analysing data. For example, a company can explore product returns relating to  certain supplierand use the AI environment to make decisions for the business to optimise the supply chain. Furthermore, streaming data from the Internet of Things (IoT) devices in real-time through secure channels enables companies to have an immediate view of operations anywhere in the world. 

However, for this to work, analytics must become a fundamental part of the company culture. It must be weaved into every aspect of the business to deliver the value required to differentiate the business. To this end, analytics can become a platform which businesses can use to thrive irrespective the market conditions. 

This article was originally published on IT-Online.

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