Quilytics provides spend analytics solutions to companies of varied sizes by uncovering buying patterns, preforming an in-depth review of your procurement data including supplier and invoice level details, rationalizing supplier information, normalizing payment terms, etc. We leverage your purchasing data and bring forth saving strategies for your company. Our solutions are powered by Artificial Intelligence that provide complete visibility of your spend data. Using our solution suite, you can discover various opportunities allowing you to make strategic business decisions. In addition to spend analytics, Quilytics also offers payment term analysis, contract management, supplier analysis as added services.

Data Framework and Infrastructure

We design data framework by mapping data from multiple sources like Epicor, NetSuite, SAP Ariba, Salesforce, etc. and establish infrastructure to store it automatically in our data storage system.

Taxonomy Classification

We classify transactions using the UNSPSC classification codes or provide hybrid taxonomy solutions. Machine learning algorithms and AI are used to categorize transactions by internally building fully functional training sets.

Analytics and Spend Cubes

Team Quilytics consists of highly experienced spend analysts who design custom dashboards to help you drive immediate savings. Our timely data refreshes of the spend cube ensures maximum efficiency and achieve tangible opportunities.

Case Studies

Use Machine Learning to transform data from ERP system to classify line-items in correct categories and rationalize supplier names to a facility services pioneer company

  • Client Introduction :

    The client is a pioneer in providing facility services across North America over the past 50 years

  • Client Challenge:

    The client’s major concern was handling uncleansed data coming from various ERP systems.

    • Product line-items were not classified in the correct Product Categories
    • There were varied supplier names which needed to be rationalized with their parent companies
  • How Quilytics helped:

    Supplier Rationalization

    • Created parent-child mapping file by looking at historic suppliers
    • Designed a python script to run each time new data was ingested in the system which cleansed the supplier base by 40%.

    Category Classification

    • Built a robust Artificial Intelligence model using Natural Language Processing and Clustering technique to bucket line-item descriptions into correct Categories
    • Accurately classified more than 1B rows of line-item with 95% confidence interval

Use Spend analytics to provide detailed information of dollars spent on material sourcing to a healthcare management company

  • Client Introduction :

    The client delivers innovative specimen and client management solutions for healthcare industry

  • Client Challenge:

    • The client had very less overview regarding their materials and supplies being procured from their suppliers. There was no proper taxonomy to classify data into Product Categories.
    • The team had no visibility on the amount spent on sourcing materials and no defined payment terms
  • How Quilytics helped:

    Taxonomy Creation and Mapping

    • Built a hybrid taxonomy by performing market research in the healthcare sector and constructed a 3-layer classification tree to help the client segregate data into relevant categories.

    Spend Cube

    • Designed a Spend Cube in Tableau with categories data
    • Indicated Top Product Categories by Spend
    • Rationalized Payment Terms and provided saving opportunities across different suppliers