How Data Analytics help business decision making

 Introduction       

            Organizations require raw data to formulate and analyze before making decisions that have effects on an organization. Adequate and relevant decisions are mandatory for upright and relevance in the competitive markets. The constant pressure put on businesses to improve their productivity and cut operational cost has seen most of them venture into technology to help save the situation.  Data analytics have come to aid in offering the much-needed reprieve to most companies. The technological advancements in analytical tools used by most companies have been the pertinent determiners of the successes attained by these organizations over their rivals. A data analytic tool transformations raw data into significant information employed by organizations to formulate relevant and practical operational insights. Research has established that tech savvy organizations have taken a leading role in controlling the market, thanks to the appropriate application of data analytics.

 Effective decisions incorporate the organization’s fundamental propelling factors at the forefront. Data analytics thus allow the organization to appropriately conceive their clients, making them develop suitable strategies that keep them and attract more. Analytics provide useful data and information that sum up most significant aspects that need to be taken into account to accommodate the customers. In addition to this, data analytics enhance the operation of organizations by establishing the key areas that play a pivotal role in the existence of an organization. Finally, remaining relevant in the diverse and flooded market requires appropriate competitive advantage strategy. Analytics provide organizations with the competitive advantage strategy that allow them to outdo their competitors.

The paper will focus on discussing the significance of data analytics in decision making for organizations:The paper focuses on the application and significance of data analytic tool in decision making.     

1.     How companies using analytic tools outperform other companies.

2.     How analytic tools help companies manage risks.

3.     How companies incorporate data analytic in their decisions to outperform their competitors by leveraging new opportunities such as product innovation, identification of new trends, and new revenue opportunities.

4.     How the speed of data analytics puts a company at a competitive edge over its competitors.

5.     How the incorporation of data analytics enables an organization to come up with a wealth of insight.

Outperformance in the industry

Companies that use data analytics tools obtain insights that allow them to identify their very beneficial clients and continue to provide them with better services[1]. Companies using data analytics tools surpass other competing companies through discovering fresh income openings, steering product novelty and finding ways of lessening fraud[2]. The speed of the application of data analytics gives a company a competing edge in the industry. Since businesses are presently not restricted to little and thin data sets, they can explore all applicable information to determine formerly unknown connections. With these new perceptions, businesses can decrease the response time of making decisions and other operations.   

Again, since companies that use data analytics can generate a rich insight, they have the potential to create the poise to operate with speed and certainty. The speed and conviction allow them more correctness, more frequently.

Risk management

Failure to rapidly obtain the correct data frequently leads to defective decisions. Additional setbacks can transpire when data moves from several silos and goes through many users in a company. To prevent such troubles, businesses require practical conceptualizations for getting the actual data, incorporating into their procedure and offering the proper means and access opportunities[3].

Since data analytics has become more vital to the creation of business advantages, there is a call for the broad protection of data. Most managers are presently taking action to apply tough protection and confidentiality of data beside control strategies for protection of their organizations from either inside or outside risks.

The Acquisition, expansion and retention of consumers.

Companies cannot risk taking clients as expansive demographic components.  At now, data and analytics are capable of assisting companies with communication with their consumers at a personal level.

Data and analytics can assist a business find and convey accurately what a client wants[4]. Through revealing significant movements that are concealed in the vast reserve of inward data and amalgamation of the data with the immense volume of available customer information, data and analytics have the potential to tackle customer wants quickly. Such high degree of personalization and reliability is what allows companies get new clients, expand the consumer base and withhold the present users[5].

The benefits of data and analytics are evident in the banking sector where customer service is more optimized through customer-centric services[6]. Through such services, customers can access loans faster and the performance of many business tasks are simplified.

Employee motivation   

The use of data analytics can already be seen in management. For instance, an organization by the name of Paschal Truck Lines employs the IBM analytics that enables it to develop predictive methods that can assist it recognize the aspects that produce high worker earnings and act on the information after that. In every month, the truck company handles about 5000 requests and employs 200 of those job seekers.

The procedure entails collection of data about the skill and past job of the applicant in the geospatial field. With the use of the Watson Analytics, the human resource managers in the company can develop connections between employment settings hence discovering small pieces of data on the ability of the driver that determine the reconstruction of fashions in hiring, revenue decrease, and large retention.

Saving travel time and optimization of costs

Among the services that businesses offer across the world is transportation. An example of transport services is one by the Caliber Patient Care, which provides client transport services from their residences and hospitals. This company applies the IBM Watson Analytics that enables it to create data on the tours that its drivers undertake[7]. Afterward, it uses the data to find new paths, which can improve efficiency with travel time and costs. The data also assist the company in developing data-directed resolutions on business travel strategies[8].

Bibliography

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[2]Mantone, Pamela S. "Overview of the Companies." Using Analytics to Detect Possible Fraud: Tools and Techniques, 2013, 1-17. doi:10.1002/9781118715789.ch01.

[3]Lobo, Bento J., Christi Wann, and John G. Fulmer Jr. "Greece: How can companies manage the new risks?" Journal of Corporate Accounting & Finance 21, no. 6 (2010), 19-24. doi:10.1002/jcaf.20623.

[4]Angeli, Federica, and Rosa Grimaldi. "Leveraging Offshoring: The Identification of New Business Opportunities in International Settings." Industry & Innovation 17, no. 4 (2010), 393-413. doi:10.1080/13662716.2010.496245.

[5]Morabito, Vincenzo. "Big Data and Analytics for Competitive Advantage." Big Data and Analytics, 2015, 3-22. doi:10.1007/978-3-319-10665-6_1.

[6]Liu, Liu, and Panos Louvieris. "Managing customer retention in the UK online banking sector." International journal of information technology and management 5, no. 4 (2006): 295-307.

[7]Olavsrud, Thor. 2016. "8 Ways IBM Watson Analytics Is Transforming Business". CIO. http://www.cio.com/article/3026691/analytics/8-ways-ibm-watson-analytics-is-transforming-business.html#slide5.

[8]Kemelor, Phil. "Becoming a Data-Driven Organization: How To Use Web Analytics To Guide Site Strategy and Tactics." PsycEXTRA Dataset (n.d.). doi:10.1037/e521612014-085.