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The Data-analytics ecosystem is expanding exponentially amid Technological advancements in the form of AI-Artificial Intelligence, IoT- Internet of things, & Big-Data. 21st Century Accountants need to understand data-analytics, in order to facilitate robust business-decision-making in their Organisations.

Business-Executives are deploying Business-Intelligence tools & applications, in order to better understand their targeted markets to outplay their Competitors. In doing so, they’re implementing the new ways of data-gathering (Google Analytics), & Business-Data-Intelligence tools (CRM).

Business Partner Role

The roles of Management Accountants are changing. They are expected to be Business-Partners; whereby they’re not only able to assimilate data from multiple sources, but are expected to draw meaningful inferences for the Business-Stakeholders.

Gone are the days, when Accountants were merely required to add numbers (trial balance). The future is all about advising your Business-Stakeholders.

Facets of Data Analytics

Following are the key facets of data analytics.

Descriptive Analysis:

What happened: under descriptive analytics we try to understand the historical performance by employing metrics e.g. KPIs – Key-Performance-Indicators, Gross profit margins, Net profit margins, & ROI – return on investment.  This type of analysis is based on the historical data.

Accountants use Microsoft Excel to calculate the above ratios & plot them on a chart for more visibility. In BI – Business Intelligence tools such as Power BI: you can add more visualizations e.g. KPI per location/geography.

Diagnostic Analysis:

Why it happened. This builds on the descriptive analytics. Further drill downs are performed to understand the root causes of underlying exceptions in the data. Furthermore, the data that’s related to these exceptions is collected & statistics techniques are deployed to resolve these data anomalies.

Predictive Analysis:

What will happen. Predictive analytics is all about future. What is likely to happen, given the scale of variables & exceptions in place. Regression, Decision-trees, & Machine learning is used to predict future viability of the projects (3YR-F’cst, Mergers & Acquisitions).

Prescriptive Analysis:

Which action to implement. Prescriptive analytics is based on the Predictive analytics. You decide which action-plan to implement under the given underlying data findings.

By analysing the historical growth plans & change initiatives, the Organisations can better understand their commercial viability. Machine Learning & advanced BI tools are vital in this analytics branch.

Cognitive Analysis: Cognitive analytics assist in reaching conclusions about the existing knowledge base (CRM). What might happen: if we were to execute a potential Corporate Strategy: this is the question C-suit executive often discuss in their Town-Halls.

Cognitive analytics is all about evaluating & assessing the viability of such strategies (Customer conversion) & initiatives) Customer retention program).

Summary:

The emergence of Online-Marketplaces, & opportunities to reach out to Global-Consumer-base is making Companies to deploy advanced data-analytics applications & tools to outplay their competitors in terms of market-share & profitability. Accountants can play a vital role by utilising big-data to their advantage.

FMCG & Service Oriented Businesses are deploying Behavioral-Data-Analytics to better understand the Customer buying habits. Accountants will have to ensure that they are able to comprehend the Big-Data to produce valuable business-insights for their Organisations.