Through the proper use of spend analytics, what companies can achieve is nothing less than magic – going all the way from increasing cost savings to enhancing productivity to streamlining processes. Throughout these activities and more, the core purpose remains to be able to successfully analyze spend analysis data and implement the changes indicated by it. In other words, the entire process of spend analysis squarely depends on the data; valid and reliable data will uncover opportunities for improvement, while unreliable data will do the exact opposite.
The Pitfalls of Bad Spend Data
Spend analysis is fast becoming a necessity for businesses in every industry. No matter how small or big a company is, the benefits of spend data analysis make it a must have. The dangers of using bad spend data should be quite clearly evident, and they may include:
Spend analysis is fast becoming a necessity for businesses in every industry. No matter how small or big a company is, the benefits of spend data analysis make it a must have. The dangers of using bad spend data should be quite clearly evident, and they may include:
- Missing Out on Opportunities for Improvement. The biggest and most dangerous risk bad spend data poses is missing out on the right opportunities for change. This includes identifying areas for cost cutting or improving profitability by transforming procurement and supply chain operations.
- Complicated Contractual Issues. Lack of reliable spend data may also cause delayed or improper monitoring of the supply chain system which may cause contractual issues. This may mean losing out on volume discounts and supplier rationalization.
- Hampering Growth. Using unreliable or disorganized spend data is a sure way to hamper an organization’s growth. From being unable to identify room for improvement to missing out on cost cutting opportunities, the implications are numerous and severe.
Data Preparation for Spend Analysis
Here are some insightful tips that can help in data preparation for spend analysis:
Here are some insightful tips that can help in data preparation for spend analysis:
Classifying Spend Data The first step in ensuring data integrity is classification. Classification of spend data across an organization must be uniform, and should preferably be based on UNSPSC standards. Some companies may use other standards for item classification, which is perfectly fine as long as the same taxonomy is carried across throughout a company. | Mapping Spend Data The second step involved in generating meaningful data is mapping based on categories and suppliers. This process essentially involves assigning items to suppliers based on geographic region, type of supplier or supplying organization, and other similar criteria. The end result is that there is a greater degree of visibility across the supply chain for rationalizing procurement and cost reduction in terms of ordering and transportation | Process Design and Integration Lastly, the data should be usable to create scalable processes and integrate with existing or new internal systems. The goal here is to create an intuitive solution that can be used across the board from managers to line employees. The compatibility of such data with ERP solutions – both current and future – is also essential in order to maximize efficiency and minimize the chance of any hiccups during expansion. |
Data is King, integrity is everything
Ensuring data integrity is the first step in taking full advantage of spend analysis at any organization. The pitfalls of bad spend data can have severe consequences, and negatively impact opportunities for growth, cost cutting, and improving profitability. By preparing data in accordance with a few simple guidelines, it can be ensured that the maximum benefit will be obtained through spend analysis. Furthermore, it also becomes easier to integrate data with ERP solutions and other management tools in order to increase efficiency and boost productivity throughout the organization.
Ensuring data integrity is the first step in taking full advantage of spend analysis at any organization. The pitfalls of bad spend data can have severe consequences, and negatively impact opportunities for growth, cost cutting, and improving profitability. By preparing data in accordance with a few simple guidelines, it can be ensured that the maximum benefit will be obtained through spend analysis. Furthermore, it also becomes easier to integrate data with ERP solutions and other management tools in order to increase efficiency and boost productivity throughout the organization.