Abstract
In this paper, I used a business intelligence solution for Tencom. Tencom is one of the largest consumer cooperation and has a digital market with more than one hundred stores in fifty nations and approximately twenty million subscribers. With the type of growth the company was experiencing, there has been an overwhelming amount of client data. The data used covered areas such as online transactions, in store transactions, and marketing demographics. However, the company lacked the necessary tools to analyze this data and come up with accurate and fast information that they could use in business decision making.
I therefore used a business intelligence approach as a solution to this challenge. Using Tableau as the business intelligence tool, data analysis was made much easier. With the adoption of the tool in the entire organization, in addition to a collaborative link between the commercial units and the information technology department, Tencom is now able to streamline the analysis of data in their operations. The improved data analysis approach improved the impact of Tencom in the market and also improved their business strategy.
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Business intelligence can be defined as the technologies, software and activities for the gathering, analysis and presentation of business data. The main application of business intelligence is to improve the process of decision making in a company or an organization. Basically, a business intelligence system is driven by a set of data through a Decision Support System (DSS). The term business intelligence is at times used interchangeably with reports, briefing books and query tools and management information structures.
In a business, the application of business intelligence is mainly to offer past, existing and future analysis of business processes, most frequently by use of data that has been stored in a data warehouse or a data mart and mostly functioning from operational data (Fan, Lau & Zhao, 2015). The software aspects of business intelligence support interactive pivot table reports, visualizations, and statistical mining of data. Software tackle transactions, output, finances and several different sources of commercial data are used for reasons that include management of business performance.
Many companies today deal with thousands of terabytes of data mainly to conduct marketing analysis. This has become a very hectic exercise even with software applications such as excel. Many companies are therefore adopting a Business Intelligence approach to address this challenge. BI is a system that makes use of services and software to change any amount of data into meaningful information that can be used to make decisions in a company and even improve revenue (Guster, D. E. N. N. I. S & Brown, 2012). Business intelligence tools gain access to pieces of data and analyze it to produce an actionable report in form of a graph, chart and even a map to offer concrete and conclusive information concerning the state of a company.
In the current business context, companies are starting to recognize that information and data cannot be grouped as different aspects of management of information, but rather should be governed in an integrated business process. Enterprise management of information combines two critical aspects which are Business Intelligence and Enterprise Content Management. In the current century, many companies are shifting towards Operational Business Intelligence that is currently undervalued and unused by many companies (Moro, Cortez & Rita, 2015). Initially, business intelligence service providers were targeting only the top companies but currently, there is a shift in the trend where they are now targeting the bottom parts of the business environment mainly focusing on self-service type of business intelligence.
In the self-service business intelligence format, there is the involvement of business structures and analysis of data that offers end users in a business access to the company’s data without the direct involvement of the information technology department. It offers end users the capability to accomplish more with the data they have without having to have any technical data analysis s skills. The proposed solution is created to be flexible and user friendly such that the end user can examine data, arrive at a certain decision, plan and make future predictions. Companies for example Tencom, have assumed an approach to making Business intelligence an easily implementable component for different end users.
OLAP (Online Analytical Processing)
OLAP is the fundamental technology that acts as an enabler of business intelligence. It is a powerful technological approach that is used in data discovery, including the ability to allow unlimited access to reports, complicated statistical calculations, and a predictive or a ‘what if’ analysis of a budget or a business plan. OLAP functions by conducting multidimensional analysis of business data and offers the ability for complicated business analysis statistics and the analysis of business and market trends. The system also allows the end user to conduct an ad hoc analysis of data in several viewpoints. This offers an insight and comprehension that end users may require to make a business decision.
In a successful business environment, there is continuous plans, analyses and reporting of sales and business processes with the aim of exploiting effectiveness, minimizing business expenditure, and improving the market share of a company. Basically the more the data a business can gain access to concerning a particular activity, the more probability they will have of improving the plans in that activity. Businesses are collecting data on a daily basis but the main challenge still remains on how to get this data to produce precise, dependable and quick information concerning the business.
Tencom is accompany that mainly deals with online shopping. The company has established itself as an international business competitor reaching customers all over the world. However, the company was faced with the challenge described above. The company had access to different data sets and formats that would have been a benefit to their commercial process. However, they were unable to get this collected data to assist them in generating accurate, dependable and quick information than they could use to make business decisions. The main purpose of business intelligence was to avoid the challenge of garbage in garbage out (Fuchs et al., 2013). This was the main challenge in Tencom and it resulted from insufficient analysis of data. It was therefore important for Tencom to adopt a business intelligence approach to address this challenge.
Additionally, to remain competitive in the e-commerce sector, Tencom had to shift from an Excel based data analysis system to a more advanced Tableau system of analytics. The system helped the company exploit Tableau dashboards to establish the most crucial insights and use them to improve client experience both online and in-store. By conducting analysis on purchasing, reactivation and subscription data measures in Tableau, the company was able to establish the tradeoffs of venturing into the retail sector compared to digital marketing. From the perspective of operations, the business intelligence team used Tableau to examine and analyze client segmentations, which offered insights on decisions such as transport methods, subscriber lifecycle handling and assortment of products by category.
For Tencom, it was crucial for them to think on how they could exploit business analytics and use it as a competitive advantage to establish insights and offer an improved experience for their clients that they have worked with for more than forty years.
Problem Statement
The company had access to different data sets and formats that would have been a benefit to their commercial process. However, they were unable to get this collected data to assist them in generating accurate, dependable and quick information than they could use to make business decisions.
Business Intelligence
There has been an existing conflict on the best definition of business intelligence. Generally, business intelligence is described as a system that collects, transforms and presents structured information from different origins, thus minimizing the time required to obtain beneficial business data and allow the efficient use of this information in decision making (Peregrine et al., 2015). This gives room for dynamic business information and classification of data into different managerial choices. Fan, Lau & Zhao (2015), depict business intelligence as a process that involves a sequence of activities being steered by the specific data needs of the decision making committee and the aim of attaining a competitive advantage.
Business intelligence is a process that converts information onto data and later into knowledge, thereby improving a business’ basic decision making procedure (Guha, Wrabetz, Wu & Madireddi, 2012). It is further classified as a structure that assists decision makers to understand the economic situation of a company. It is also described as a group of statistical and methodological designs from analysis used for mining data and beneficial information from raw data for helping in the process of decision making (Guster, D. E. N. N. I. S & Brown, 2012). It assists the management by breaking information from different sources into understandable bits at the tactical and the strategic level.
A data warehouse in business intelligence is used to gather data from different sources into one site by use of the extraction, transformation and loading process (Moro, Cortez & Rita, 2015). A data mart is generally described as a smaller warehouse that stores information form one department rather than the entire company.
Several studies state that failure to implement business intelligence in an organization is mainly blamed on the lack of conformity between the organizations proposed business intelligence system and the objectives and goals of the organization. According to Laursen & Thorlund (2016), business intelligence can be analyzed from both an organizational and a technological perspective. Technological business intelligence capabilities mainly emphasizes on the quality of data. Organizational business intelligence on the other hand emphasizes on the application and implementation of business intelligence in an organization and examines elements such as the flexibility of the model and the risks and goals that may be realized (John Wiley & Sons. Larson & Chang, 2016). Business intelligence mainly depends on structured and/or numerical data. Laursen & Thorlund (2016), state that the quality of data is the most crucial elements in the success of a business intelligence model.
Methodology
The methodology involved both a quantitative and a qualitative approach. We started with a preliminary analysis of the business setting and the problem which we divided into work units that were easier to analyze. Through Tableau dashboards, Tencom’s business sections from the operations to the marketing section collect data from a Netezza data warehouse that contains more than seventy five sources of data ranging from Google Adwords, FedEx, point of sale and others. With all the collected data in one location, they are able to analyze the entire client process form the purchasing trends to marketing engagement.
Using tableau, as the data visualization tool, the data is continuously analyzed and the results obtained. The data is in a master worksheet and does not therefore require any consolidation. Prior to analysis, the data is cleaned eliminating all the duplicates and highlighting errors. Using the tool the scenario is analyzed and the challenges encountered by Tencom highlighted. The data set contains both numerical, quantitative, qualitative and time stamped data.
Findings
There has been evident growth in both in store and online sales of the company after the implementation of business intelligence. Initially, Tencom used eighty percent of their time and resources I the process of data preparation. However, after implementation of Tableau, data analysis has been made easier for the company. The software is able to cut fifteen to twenty hours per week for data analysts and scientists.
The company has upwards of 1100 dashboards shared over the Tableau server introducing accessibility and scalability to their analysts and data experts. Currently, the company mainly emphasizes on evergreen reporting and tableau dashboards that have a web functionality. Evergreen reporting, means that data is delivered daily, weekly, monthly and annually using a system of client metrics. This helps every department in the organization, including the executive, implement plans, examine their impact on the determined metrics and make the necessary changes.
The data indicates that with the implementation of business intelligence in the company, there will be a 61% annual growth within the next five years and a 6.4% monthly turn over in profits. An increase in evident after the implementation of business intelligence.
Due to the current shift in consumers, mainly in the physical stores to an online platform, one of the most crucial things that business intelligence has enabled in the company is the capability to gather the data accessible to the company, put it into tableau, obtain insights and have the acquired insights drive their business strategy and drive a more improved client experience. The company has been able to create a collaborative culture mainly between the business units and the information technology department.
Conclusion
With the implementation of business intelligence, it is evident that there has been a big and notable transformation at Tencom. The different departments in the organization have now become devoted to forming a culture of analytics in the overall company. This has had an impact even in the management of the company. Using tableau as the key enabler and as a business intelligence tool, Tencom has been able to educate its analyst, executives and every department on the significance of data insights. The executives have also noticed the positive impact of business intelligence in the company and recognized the implementation of Tableau as a vital element in the daily and strategic operations of the company. The journey of Tencom to an analytics culture has involved crucial investments in the preparation of data and data sources creation and offering beneficial insights. This has significantly improved the speed of business and is critical for Tencom to achieve their mission.
References
- Fan, S., Lau, R. Y., & Zhao, J. L. (2015). Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2(1), 28-32.
- Fuchs, M., Abadzhiev, A., Svensson, B., Höpken, W., & Lexhagen, M. (2013). A knowledge destination framework for tourism sustainability: A business intelligence application from Sweden. Turizam: međunarodni znanstveno-stručni časopis, 61(2), 121-148.
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