Data Plays a Huge Role in Decision Support Systems

Specialties in areas such as customer intelligence systems, decision support and business intelligence are perceived as too technical for the average company. However, they are important pillars in improving the profit earning capacity of a business.

The idea that data could be used as intelligence system in business was around since the mid-90s. However, it is still a growing field and emerges from increasing competition in the market. It is now more of a necessity to simplify the complex business climate.

Business intelligence systems have also made serious in-roads in green businesses where they allow companies to evaluate their efficiency in terms of a reduced carbon footprint.

Significance of BIS

There is an ongoing debate whether intuition plays a major role in decision making or is it the analytics and a rational approach. While decision making through analytics makes sense, still a number of business owners follow the intuition approach.

Business Intelligence Systems (BIS) are slowly becoming a major stakeholder in the market. The Analyst Technology reports that the market of BIS has grown by 10.5% from June 2012 to June 2013.

It further suggests that BIS is the area where most businesses look to make an IT investment in the coming year or so. An excellent example of this can be seen in setups where customer intelligence systems (CIS) are being integrated to optimize demand generation services. As the marketing plan based on such systems are based on consumer intelligence, it allows for execution of multi-channel marketing at the appropriate time. Furthermore, the sophisticated elements and analytics improve customer retention and acquisition rates.

On a related note, ‘Green IT’ is also an evolved form of CIS. It shouldn’t be confused with energy efficiency measures taken in the IT industry. It refers to using business intelligence for green setups and for companies to improve their energy consumption. Deloitte Consulting LLP is a valid example of a business that has introduced ‘sustainability analysis’ customized for green setups.

Many business owners tend to think that enterprise resource planning (ERP) is BIS. However, it is just one application. The real asset of BIS is its usage in decision making. Data has business value which is generated only if it analyzed and used. A survey done by MIT highlighted that 60 percent of manager believe that their information capacity is huge; it’s the information utility that they lack.

Focus on Utilization

Using data for decision making is essential because in the coming years, this would be vital for the sustainable future of businesses. If you are using IT systems for mere transaction processing, then you are wasting a good return on offer. The BIS is designed for query and analysis.

If you are using data to your benefit, then the business/customer relationship, internal process efficiency and customer intelligence would improve. For instance, the supplier/partner relationship is important in business. Using data, there is reduction of transaction costs and coordination in the form of higher responsiveness on your end. In return, there would be an improvement in the inventory turnover.

Another way to explain is how the data can improve the profitability of your company. There are always some niche customers who are adding to profit margins. If the standard profit increment is applied without segregating their data, there can be flaws in the number. This is because the total cost satisfying each customer is different. BIS helps in segregating them using a trend based method.

Green businesses in particular can take benefit because their customer base is much targeted, thus BIS would help them maximize profit. SiSense Prism is a valid example of company that is using business intelligence not only to develop cost saving green workflows, but also targeting a niche stakeholder in the form of government agencies and green welfare communities.

Companies and business owners should focus more on statistical modeling techniques like predictive models. They use existing data to present preemptive situation, which allows you to act before time. Predictive models assist is better control over the market fragility and empower you to monitor systems in a secure environment.

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