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Singapore - Corporations and government agencies on the eRFP bandwagon are more than pleased with the results, but should seriously consider integrating business intelligence into the eRFP best value source selection process for the best results. How? Sam Adhikari finds out.
Best value source selection methodologies involve Request For Proposal (RFP) processes. Evaluating proposals to determine the best value is a complex process. Procurement practitioners create endless models in spreadsheets to manage this process. The purpose of the eRFP project was to establish a set of standard methodologies and tools for evaluating diverse RFPs without building endless models in spreadsheets. The biggest problem in RFP evaluation is that every RFP can be different from another and the evaluation model may require a change from RFP to RFP. Every corporation, NGO, or Government agency evaluates RFPs in a somewhat different way. Business Intelligence (BI) methodologies were used to standardise the applications, practices, and technologies for the extraction, translation, integration, analysis, and presentation of data to support improved decision making in best value selection process. Corporations, government agencies and other organisations that use eRFP report positive results. However, implementing business intelligence and group decision support systems in best value sources selection processes have their own pitfalls. The biggest challenge is to train the proposal evaluators in using online evaluations tools. User-friendly interfaces and intuitive processes help in achieving evaluator efficiencies. Just like any other BI process, eRFP required good planning, and implementation strategies.
The ability to easily identify the "best qualified" firm or proposal is a very complex process. It involves selection of right criteria, metrics, subject matter experts as evaluators and an evaluation process that just suits the corporate or agency procurement process and mythologies. The best practices as defined in IT governance guidelines differ from RFP to RFP. That necessitates use of advanced business intelligence techniques to create standardised processes for efficient best value proposal evaluation.
In this project, a software configurator, a web based group decision support system, an evaluator interface, a productive reporting interface, and an online vendor data submission interface create a flexible environment that is capable of evaluating any RFP using a flexible evaluation process. The challenge is to establish a business intelligence environment that allows for flexibility in the process and at the same time save cost, effort and time of the practitioners. The use of the system to facilitate the RFP evaluation process enables practitioners to reduce the time and cost of proposal evaluations, reduce the subjectiveness of evaluations, provide a complete audit trail, eliminate paper intensive processes, and increase evaluator efficiency.
A flexible decision support engine takes its final shape based on the template used in the configurator. This makes this architecture unique because need for IT maintenance and programming is substantially avoided. The decision support system is flexible and follows the template under use. The project administrator (normally the buyer) creates a project in which specific details about a vendor selection/RFP evaluation process is selected. The project administrator can assign tasks to evaluators, view progress, and generate intelligent reports. This decision support engine allows multiple iteration of evaluation. The evaluation process can be segmented into initial/written, oral/presentation, and risk assessment. The architecture also allows for multiple iteration of evaluation. Based on the template metrics these evaluations can be combined for an aggregate rating. The engine allows for standard workflow to shortlist proposals. It also has many cost models which makes the evaluation process further flexible. At any point of time, the buyer or project administrator can view the overall progress of the evaluation. The architecture allows flexibilities in task assignment to evaluators. Different evaluators can evaluate different part of the evaluation process such as Technical criteria, Personnel criteria, Past Performance criteria and Cost.
The college was successful to utilise the eRFP system with statewide RFP for 403(b) providers.
In 2008, the Internal Revenue Service in the United States finally passed 403(b) legislation that required employers to comply by January 1, 2009 with numerous new 403(b) laws and regulations as well as define which specific 403(b) product providers each employer would list in their 403(b) plan document.
Florida State College at Jacksonville was asked by the State of Florida Council of Human Resource Officers (28 colleges) to be the lead institution to co-develop a RFP, solicit all national 403(b) providers and support a nine different college evaluation committee located in nine different cities in the State of Florida. The college utilised the eRFP process.
The nine college evaluation committee had never used the eRFP system, which they trained in less than 30 minutes by a conference call to be online evaluators. The college received 26 different 403(b) company proposals, which were evaluated by the nine colleges. The nine committee members in nine different cities successfully posted to the web based eRFP system their scores, participated in two public evaluation meetings, an interview, and a negotiation session.
The results of the eRFP process was impressive in that the solicitation allowed the entire State of Florida system to leverage our cumulative US$46 million a year in 403(b) contributions to achieve not only full IRS compliance but very significant reduction in fees and charges our 42,000 statewide employees had been paying 403(b) providers.
Comments from both the nine college evaluation committee and 403(b) provider companies were that they were impressed with both the functionality of the eRFP system and the ease of use, which saved significant travel cost and time for the nine college committee members.
Rockland County, New York, like most other government agencies had seen their use of the Request for Proposal increase significantly over the past five years. Already issuing over 225 Competitive Bids on an annual basis, Rockland began to see the number of Requests for Proposals issued each year reach an average of 50 - 60. Along with the increased use of the RFP came many operational issues including, how to manage multiple evaluations being conducted at the same time, how to ensure thorough, independent and objective evaluations by multi-disciplinary teams, how to take evaluation data from paper rating forms and roll that information up to meaningful reports that can assist the evaluation teams in making informed decisions, and how to document the decision making process so that the source selection decision can be justified to administrators and elected officials.
Rockland County determined that it needed an automated group decision support system to help manage the RFP evaluation process. They have used eRFP process to implement best value selection process. Since implementing the eRFP evaluation system the County has come to rely on the use of this on-line evaluation tool to make better sourcing decisions. The system is database driven and uses the most current web-based technologies. The software is deployable through an organisation's Intranet or through the Internet. Internet access allows evaluators in many different locations to easily evaluate the same proposals. Since the software is web-based, it also allows evaluators access from their home computers. Allowing evaluators to work from home while evaluating proposals can lead to more in-depth evaluations, usually in a shorter timeframe.
eRFP is a Business Intelligence (BI) application. It uses extract-tranform-load (ETL) process to pull data from various data sources to populate and maintain the BI data warehouse. It also uses intelligent and flexible reporting and query tools. The resultant formatted data, graphs, and charts are extremely useful in best value source evaluation, and risk mitigation. It also uses online Analytical Processing (OLAP) tools to analyse multidimensional data from many different perspectives. eRFP uses drill down analysis to examine high level, summary data in increasing detail to gain insight into certain elements in the best value source selection process. Data mining methodologies employed within eRFP model explore large amount of data for hidden patterns to predict future trends and behaviors for use in decision-making processes.
The biggest challenge in implementing eRFP is the evaluator training. Interestingly, Florida State College at Jacksonville, Florida, reports that the nine college evaluation committee had never used the eRFP system, which they trained in less than 30 minutes by a conference call to be online evaluators. Once evaluators get accustomed to online evaluations, they tend to discard the paper based processes.
The other challenge in implementing eRFP is to make sure that the data is transferred across the Internet via secured technologies. Secure Sockets Layer, Firewalls, and Virtual Private Networks help in this area. The authentication process and database security is also critical.
About the author:
Sam Adhikari teaches Information Technology, Supply Chain Management, Procurement and Decision Support Systems at Rutgers University's Business School.
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