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Elevating Business Intelligence For Smarter Spending

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Armin Roeseler DirectBuyIn its original state, Business Intelligence (BI) existed as a “reporting function” that delivered summaries of historical operational data to decision makers. The summaries provided were beneficial at one time, as they paved the way for future corporate spending decisions.

In today’s ever-evolving digital economy in which retailers operate, the past and its associated data no longer provide an adequate guide to predict the future. This primitive BI approach can be compared to driving a car by looking in the rear-view mirror; the driver attempts to anticipate the terrain in front of the car based on what has been experienced and observed in the past. Instead, retailers must identify predictive analytics within their BI infrastructure that help answer the “what if” questions relating to the future.

Benefits Of BI Implementation

Although the task of implementing new and effective BI solutions might seem ominous, the benefits have proven to be incalculable as they present opportunities to find considerable savings in a fast, intuitive and graphical way. Beyond product buying and purchasing, retailers can leverage BI solutions for numerous functions, such as providing better customer service initiatives, reducing ineffective marketing costs, improving the supply chain and more.

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BI analytics have also consistently been shown to boost sales and create more personalized relationships with customers, among other benefits. In fact, 54% of retailers say using data tools seriously boosted 2014 revenues by helping them make smarter product buying decisions, according to Lightspeed’s 2015 Tech Trends Survey. The ROI companies are receiving from BI implementation is also substantial. New data from Nucleus Research found every dollar spent on BI solutions receives a return of $10.66.

Building A Sustainable BI Framework

Assembling a viable BI framework that aligns directly with company goals and objectives is more vital than ever before, as BI solutions continue to be a major priority for enterprises across the country. A Gartner survey showed Business Intelligence and analytics remain the No. 1 investment priority of more than 2,800 chief information officers for the fourth consecutive year. If executed correctly, a BI setup can help identify inefficiencies, measure performance and uncover opportunities.

However, despite the nearly $114 billion spent toward advanced BI technology, adoption is still abysmal. According to Forrester, more than 60% of business and technology decision-makers reported time concerns with creating and updating dashboards. And with retailers under more pressure to increase sales and reduce costs, the implementation of new predictive analytics is becoming more common in their efforts to vigorously regulate a pattern and predict future outcomes.

Predictive analytics can be described as a practice of extracting information from historical data to determine a pattern and to predict the future. It utilizes a variety of statistics, modeling, data mining and machine learning techniques to study recent and historical data. Regardless of its incapability to predict what exactly will happen in the future, it can forecast what might occur. Often, predictions about the future are accompanied with a confidence interval, e.g. “Sales will increase between 3% to 5% in the next year, with a certainty of 98%.”

In addition, predictive analysis provides a clear meaning to the data and creates opportunities for business to be profitable. For example, Tesco employed a BI platform that incorporated weather information into its store operations to better predict effects of weather on sales. This allowed them to adjust the supply chain accordingly.

Allocating Budgets Based On BI Analytics

Given the way customers are rapidly evolving, an elevated BI function is essential to budget allocation decisions. This data is precious, as retailers can determine what shopping portals are driving the highest amount of revenue, how customers prefer to be serviced, what products are contributing largely to purchasing volume and more.

Marketing departments with data-driven infrastructures have benefited greatly, as BI functions can provide necessary insights on where marketing dollars receive the highest return on investment. Not only can a marketing team use these metrics to pinpoint the most revenue-driven campaigns, promotions and website activity, but they can also identify and exterminate those initiatives producing unproductive numbers.

The same goes for sales. BI software can be used for analyzing the steps and time length or duration inside a broad number of customer opportunities within the sales pipeline. If advanced software isn’t being elevated, managers are left in the dark on which sales techniques are producing the highest monetary value. Instead, brands can utilize this data to retarget energy and dollars that are yielding the best results.

BI software also has the ability to bring together countless departments within a company collaboratively. For those companies that are not data-focused, questions on where the business’ problems truly lie can stir needless internal tension. Retailers need to dissect the data to see where the trouble really lies. Then, departments must work together to resolve issues and advance business procedures.

Next Steps For Businesses

Looking into the future, the advancement of BI solutions will only continue to evolve. The allure of BI is that it has the potential to turn around a retailer’s bottom line and inspire new opportunities for business. As 2015 comes to a close, it’s time for retailers to focus on how to better elevate BI in their corporate environments, as its benefits are never-ending.


 

Armin Roeseler is the CIO of DirectBuy, Inc. where for over two years he has been transforming the IT organization and technology infrastructure of the company. Roeseler has also held executive technology positions with international financial services firms and research institutions, including Bank One Corp. (now JP Morgan Chase), ABN AMRO/LaSalle Bank (now Bank of America and Royal Bank of Scotland), and subsidiaries of Lehman Brothers, Barclays Capital, and Bank of New York.

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