Introduction
The professionalism of a specialist, especially in the field of business, is determined not only by experience but also by available skills. Their quantity, as well as their specificity and uniqueness, are equally important. In particular, they are necessary for different assessments and calculations of varying degrees of complexity, one of which is spend analysis. Researchers note “spend analysis is the process of identifying, gathering, cleansing, grouping, categorizing and analyzing your organizations spend data with a goal of decreasing procurement costs and improving efficiencies.” (JAGGAER Staff, 2016, para. 1).
It is also important to understand structural techniques such as Six Sigma the possibility of implementing analytical systems beyond just one business sphere. This paper will examine the significance of data analysis skills and other commercial areas in relation to spend analysis, as well as Six Sigma’s methodology of spending patterns identification and improvement.
Data Analysis Skills and Spend Analysis
Data Analysis Skills Categorization
First, it needs to be clearly defined what data analysis skills are to explain their importance further. One of the primary skills is knowledge of systems and engineering processes. In addition to the ability to understand and interact with data, this category also includes expertise in multiple programming languages (Government Digital Service, 2020). The next point is communication knowledge, which is usually divided into leadership, team, and interpersonal.
The group of abilities of the general multidisciplinary business knowledge is also crucial. One can single out an understanding of the logical approach, planning, attention to detail, and absolute accuracy. Analytical skills, such as a high level of mathematical knowledge and problem solving, play a significant role. All this knowledge is combined and applied in the form of various analytics and analyses.
Importance of Data Analysis Skills
The skills listed above are necessary for conducting regression and Pareto analyzes, which are parts of the spend analysis. Computer programming skills are especially crucial in another approach to spend analysis, namely in exploratory data analysis, which requires the ability to competently manipulate, visualize, and report information (Ghosh, Nashaat, Miller, Quader, and Marston, 2018). Cost analysis also involves compiling and using different types of analytics. Communication skills determine the effectiveness of prescriptive and pre-emptive analytics, whose goal is to optimize and test current and future business processes (Sivarajah, Kamal, Irani, and Weerakkody, 2017).
General multidisciplinary business knowledge through descriptive analytics develops a clear picture of the current business climate. Mathematical calculations determine estimated future costs and benefits in the framework of predictive analytics. Each data analysis skill is essential for every aspect of Spend Analysis, which generally forms and explains their significance for this business procedure.
Six Sigma, Spending Patterns, and Improvement
Identification through Six Sigma methodology
The Six Sigma methodology is essentially a stepwise program to improve the effectiveness of the organization’s business processes. One of the five critical points of this business strategy, namely the third step, which involves the analysis of the process, is suitable for identifying cost structures. This procedure consists of the study of correlations and the identification of causes between all factors of business activity.
To achieve these goals, a specific diagram is used. The cause-and-effect diagram classifies the reasons according to the effects studied (Bozarth & Handfield, 2016). Often, interested specialists choose items such as manpower, methods, materials, machines, and measurements as categories (Bozarth & Handfield, 2016). Upon completion of the composition of this diagram, the Six Sigma group may notice all relations of business factors, which allows them to identify the current cost structure.
Improvement Opportunities and Six Sigma
The Six Sigma Methodology is also useful in developing opportunities to improve processes in an organization. Professionals use root cause analysis to identify such opportunities. This type of analysis involves collective brainstorming, which is divided into three stages (Bozarth & Handfield, 2016). The first third of the process involves a general open offer of all possible causes of the actual costs.
The second stage is called “Five Whys,” during which the participants in the research group ask a series of following specific questions until they reach the root cause (Bozarth & Handfield, 2016). The final step is that specialists verify the found reasons with the current statistical data of the organization. Further, the analytics identify the available improvement opportunities by correlating the available results with the desired effects.
Spend Analysis and Other Fields of Business
Spend Analysis and Operations Management
From a personal point of view, one of the functional areas of a business that needs to be included in spend analysis is operations management. According to Wang, Gunasekaran, Ngai, and Papadopoulos (2016), “big data can provide unique insights into, inter alia, market trends, customer buying patterns, and maintenance cycles… lowering costs and enabling more targeted business decisions.” (p. 98). Such an implementation will systematize and improve the supply infrastructure, reduce delivery costs and materials as well as time costs.
Spend Analysis and Technology Management
Technology management can also be considered as a possible “participant” in the analysis under discussion. It is due, according to Saunders and Brynjolfsson (2019), “a company’s intangible assets — especially those related to information technology — are not well captured on corporate balance sheets.” (p. 83). Analysis of the expenses in this area allows you to timely update the software and hardware equipment of the company, as well as to identify, improve, or reduce costly technological strategies and systems in advance.
In combination with operations, this will also enable the efficient selection of the least costly and most relevant technology suppliers. From a theoretical perspective, spend analysis can be applied to all functional business aspects, which will solve not only organizational but also global economic problems. The prediction stone is only to find the right parameters, variables, and principles of relationship.
Conclusion
This work explores the essence of the impact of data analysis of skills on cost analysis and the possible applicability of the Six Sigma methodology to optimize the organization’s business processes. Four fundamental skill categories and their interesting points were highlighted. They are knowledge of systems and engineering processes, communication knowledge, abilities of the general multidisciplinary business knowledge, and analytical skills. Their importance is explained by their need for making such components of spend analysis as regression and Pareto analyzes, Exploratory Date Analysis as well as various analytic methods.
These methods include pre-emptive analytics, descriptive analytics, and predictive analytics. Also, using a coherent Six Sigma strategy, methods for identifying spending patterns and opportunities to improve business processes were explained. These patterns can be detected through the analysis part of the Six Sigma methodology, especially the cause-and-effect diagram. The search for opportunities for improvement is mostly facilitated by a three-stage root causal analysis, the essence of which is collective thinking and dialogue. The applied practice of spend analysis is possible for functional business sectors such as operations and technology. However, this proposal was considered only from a theoretical perspective.
References
Bozarth, C. C., & Handfield, R. B. (2016). Introduction to operations and supply chain management (4th ed.). Upper Saddle River, NJ: Pearson.
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Government Digital Service. (2020). Data analyst. Web.
JAGGAER Staff. (2016). What is Spend Analysis? Web.
Saunders, A., & Brynjolfsson, E. (2016). Valuing Information Technology Related Intangible Assets. Mis Quarterly, 40(1), 83-110. Web.
Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of big data challenges and analytical methods. Journal of Business Research, 70, 263-286. Web.
Wang, G., Gunasekaran, A., Ngai, E. W., & Papadopoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International Journal of Production Economics, 176, 98-110. Web.