BUS307 Week 3 Assignment Sample Essay. Explain in detail why data analysis skills are so important to spend analysis.
Describe how a structured process such as the Six Sigma methodology (Chapter 4) can be useful to identify spending patterns and opportunities for improvement.
Recommend which functional areas of the business, such as finance, should be involved in spend analysis efforts, and justify the rationale for your choices.
Data Analysis Skills in Spend Analysis
Date of Submission
Data Analysis Skills in Spend Analysis
Spend analysis is when organizations analyze their past spending data to gain visibility, compliance, and control over their spending patterns (Pandit & Marmanis, 2008). Basically, from the data collected in procurement, spend analysis coordinates this information through suppliers ranking, commodity positioning, and the spend amount to develop a verified spend category, establish opportunities for strategic sourcing, and find opportunities for cutting down expense costs via strengthened compliance (Pandit & Marmanis, 2008). However, as Limberakis (2012) notes, successful spend analysis is not merely dependent on an organization’s ability to access, organize, and analyze spend data. It requires the integration of various key factors such as definitive data processes and data analysis skills. Through spend analysis, organizations seek to answer questions about each commodity’s spending cost, the value of suppliers based on their rank, spending trend, the amount spent on contracts, and the rank of commodities based on the amount spent.
According to Zielinski (2019), “data analysts have an ability to analyze workforce data and extract insights for line managers, in addition to other data management skills” (para. 18). Data analysis skills play a significant role in spending analysis. First, data analysis skills provide spend analysis with fully automated systems for generating spend data, promoting better quality data collection (Limberakis, 2012). A successful spend analysis call for quality and accurate data. Therefore, data analysis skills such as pulling data from an organization database ensure insights generated from spend analysis are factual and correct since they are modeled from quality and accurate data.
The extraction of data is the first and most crucial step in spending analysis. Extraction of data includes extracting spending data from multiple sources, which plays an integral part in achieving visibility in all levels of spend analysis (Pandit & Marmanis, 2012). However, data extraction from various sources can challenge spend analysis. Limberakis (2012) discusses that data compatibility is lacking because spend analysis uses data extracted from multiple systems which are not compatible. Data analysis skills such as knowledge of data analysis tools and experience with operating systems are required to ease data extraction and integration. To reduce the workload of lack of data compatibility, data analysis skills ensure that organizations use compatible data collection systems, making it easier to integrate the spend data for analysis. In addition to data extraction, data analysis also aids in cleaning and enriching data used in spend analysis.
An effective spend analysis is marked by drawing insightful insights from the analysis and achieving visibility of all spending patterns. With data analysis skills, spend analysis reduces the probability of releasing detailed results that are hard to read or interpret. Organizations need to have a clear snapshot view of spending patterns from spending analysis. A standardized system increases the capability to combine larger categories into subcategories, making interpreting results easier (Limberakis, 2012).
Identifying Spending Patterns using Structured Processes
Structured processes such as the six sigma methodology can identify spending patterns in an organization. A six sigma methodology takes place in a project in six phases, define, measure, analyze, improve, and control (Gaikwad et al., 2016). The phase of define, it includes identifying a problem, defining requirements, and setting goals. While in the phase of measure, includes validating a processor problem, refining the problem, and measuring key steps (Gaikwad et al., 2016). Suppose an organization wants to identify and evaluate its spending patterns, it can use a six sigma methodology using tools such as a process map. A process map includes determining the process boundaries, listing the steps involved, ranking the steps, utilizing the correct symbols, and checking the work or the process (Purdue Online, 2021). A process map of identifying an organization’s spending patterns will include listing all the spending categories of an organization, from suppliers, employees, operating costs, utilities to fixed expenses. After listing all the spending categories, the next step is to identify each category’s spending amount for the past months or years. The next step is ranking these categories from highest to lowest. Mapping the spending patterns of each category will help identify the spending habits of an organization as a whole and as a process, from start to end, concluding spending patterns. BUS307 Week 3 Assignment Sample Essay
Six sigma can also identify opportunities for improvement in an organization’s spending patterns. The improvement phase of the six sigma methodology includes developing ideas to remove, determining the root cause, testing solutions, standardizing solutions, and measuring results (Gaikwad et al., 2016). 7 QC tools are examples of six sigma improvement tools that can improve an organization’s spending. 7 QC tools are the seven basic tools for process solving and improvement; they include “check sheets, graphs, histograms, Pareto charts, cause-and-effect diagrams, scatter diagrams, and control charts (Neyestani, 2017). From a simple check sheet, an analyst can tabulate the spending data of an organization and use it for further analysis. For example, to identify opportunities for improvement by reducing the production cost and increasing profits, an analyst will draw data from check sheets, data such as the amount spent on production for the past year and the amount generated in profits. A comparison of production cost and revenue generated in an organization will guide the analyst in determining whether the organization is making losses or profits and needs more control over its production or expense spending.
In addition to identifying opportunities for improvement, an effective spend analysis calls for knowledge management, which includes an organization creating common standards (Limberakis, 2012). Creating common standards entails establishing accepted definitions of spending data and using these definitions to determine opportunities for improvement. According to Limberakis (2012), determining how accepted definitions are used in identifying opportunities for improvement “begins with the creation of enterprise-wide classification schemas for products and services spent through commodity codes being leveraged within the organization” (p. 16). Similar to how the extraction of data from multiple sources that are not compatible can lead to a lack of data compatibility, it is the same way the use of different language and definitions among spend data stakeholders can challenge the spend analysis process. All spend data stakeholders should agree on acceptable language and definitions or taxonomies for spend analysis.
Spend analysis integrates data from various functional business areas such as procurement, finance, IT, supply chain. Considering that spend analysis consists of data from multiple spending sources in a business, it requires integrating data from these sources to gain thoroughly researched and analyzed data for better decision making. IT in business plays a part in integrating data from various sources, ensuring data compatibility. BUS307 Week 3 Assignment Sample Essay
Gaikwad, L. M., Teli, S. N., Majali, V. S., & Bhushi, U. M. (2016). An application of Six Sigma to reduce supplier quality cost. Journal of The Institution of Engineers (India): Series C, 97(1), 93-107.
Limberakis, C. G. (2012). Spend analysis: lessons from. Supply Chain Management Review, 16(2), 10-19.
Neyestani, B. (2017). Seven basic tools of quality control: The appropriate techniques for solving quality problems in the organizations. Available at SSRN 2955721.
Pandit, K., & Marmanis, H. (2008). Spend analysis: The window into strategic sourcing. J. Ross Publishing.
Purdue Online. (2021, May 11). What is a Six Sigma process map? https://www.purdue.edu/leansixsigmaonline/blog/six-sigma-process-map/
Zielinski, D. (2019, May 28). Buy, build or borrow? How to develop data-analytics skills in HR. SHRM. https://www.shrm.org/resourcesandtools/hr-topics/technology/pages/how-to-develop-data-analytics-skills-in-hr.aspx