Spend Analysis

Spend analysis is defined as a systematic procedure that covers the collection, cleansing, classification and analysis of all the data relating to the expenditure with the sole purpose of reducing the cost of procurement, improving the work efficiency and monitoring the compliance of the work with established standards.

The best application of spend analysis can be explored in the business horizons such as budgeting and planning, inventory management as well as product development. The crux work areas of spend analysis are visibility, analysis, and process. These three elements define an organization’s crucial expenditure related queries pertaining to actual spending, areas of work expenses and return on investment. Expanding its dimensions, spend analysis can be expanded in domain areas as spend management that takes into account the spend analysis, strategic sourcing, and commodity management.

Profitability is the ground basis around which the core business activities revolve and which also defines the work areas for spend analysis. Spend analysis supports the discovery process of untapped savings by performing detailed analysis and indirectly reducing the work cycle time.

Spend Management Solutions

An organization has to face the blow from the earth when cleansing and classifying the data relating to company expenditures. You may be consolidating the expense data to develop a spend cube or collecting expense data on a particular work area category which takes the maximum work time with delayed outputs. An organization is usually faced with inaccurate data due to automated data collection and classification tools. In the end, organizations have to face out of budget scenarios for data collection activities due to various reasons.

SoftNis has outshined among the procurement spend management service industry by delivering high-performance results for a huge client base. We collect, analyze and report data ensuring that all the standards are complied with to provide for zero grounds for any data misuse or misrepresentation. We serve clients with following services:

  • Supplier list standardization and classification using UNSPSC.
  • Cleansing, classification and standardization of all sorts of expenditure data.
  • Yearly, half yearly and quarterly data analysis.

Our esteemed organization will provide you with a satisfied service experience for collection and classification of spend data for an increased profitability of your organization.

SoftNis, one of the Leading Spend Management Company provide you with efficient and affordable services for spend data transformation and provide a reliable source among the industry leaders. Our work process has been classified under the following heads:

  1. Spend Data Identification:

    Under this head, we collect the Spend data from organization’s ERP system, P-cards, and legacy systems. We source our activities for collection of all the work related areas to match the expenditures with their operations and further defining the areas of operation for the organization.

  2. Spend Data Cleansing and Standardization:

    Though data collection completes the major part, yet, data cleansing is equally crucial to rule out the unnecessary parts and map the rational data for the organization.
    We at SoftNis understand the common errors within product database since each company faces its own set of challenges and common mistakes. READMORE…>>

  3. Spend Data Classification:

    At SoftNis, we use required classification tools to focus on the company goal achievement. United Nations Standard Products and Service Code is a products and services classification for use in e-commerce and Spend Management activities. READMORE…>>

  4. Supplier Classification:

    Under flexible mode of supplier classification, the profile of the supplier is divided on the basis of validity criteria that are defined by the organization say as in form or region or purchasing category. READMORE…>>

  5. Reporting:

    We further prepare the reports to be used for future reference and predictions by the organization for expenditure data.

Contact Us to get done Spend Data Samples