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Putting Your Best Foot Forward: Using Data Analytics to Inform the RFP Process Before it Even Begins

The value of data to proposal and sales teams isn’t a secret – but many of them aren’t using the data provided by proposal automation software to its fullest extent. Teams of all shapes and sizes use data to look back at how a particular request for proposal (RFP) process went; according to a Qvidian-conducted survey of proposal and sales professionals from large U.S. companies, 62 percent of respondents use data insights to track the time it took to create proposals and RFPs. However, many fail to realize how to harness those insights to inform future business decisions.

For Cisco Systems, leveraging data analytics to inform future processes is a part of everyday life. According to Senior Systems Engineering Manager Flavio Zanetti, the company uses data analytics to predict scenarios that might happen. “We have analytics that show us specific regions and locations where our field teams are leveraging or selling our service more, and specific architectures that are becoming more relevant. We use those models in order to plan coverage and future investments,” he said.

There is tremendous opportunity for businesses to leverage analytics in RFP/bid selection to become more strategic and more likely to win deals. Advanced data analytics can empower organizations to identify which deal teams are best suited for building particular RFPs; which responses have performed the best in the past for particular deal types and questions; and most importantly, which deals take priority.

Here’s how proposal and sales teams across industries can—and should—apply data analytics to their RFP processes.

Who are the best people?

The RFP process requires collaboration between many people across offices and departments. In fact, 75 percent of survey respondents typically work with at least four other people on a single RFP or proposal. With so many team members involved in so many different projects, it’s important to determine who is best fit for which type of RFP.

Data analytics can help determine which teams and individuals have a winning record so that proposal managers can assign strong players to important proposals. Sales and proposal managers can track performances to pinpoint both the rockstars and the team members who need more support. Looking at metrics related to how often content is refreshed, productivity in terms of volume and contributions, adherence to deadlines, etc. can highlight areas of strength and areas in need of improvement. Managers can also analyze individual team member expertise to create a more strategic team with insights from a variety of industries, products and services.

The Cisco team regularly uses performance analytics. “We look at insights that tell us what happened and why, which helps us calculate our capacity and headcount planning to cover the RFP service overall,” notes Zanetti.

Understanding the strengths of individuals involved in the process is a hugely beneficial insight in planning how to tackle the next RFP. With clear visibility into which employees are excelling and which need more practice, sales and proposal managers can pair team members who need mentoring with more experienced colleagues and appropriately delegate work to ensure important projects are being prioritized—and won.

What are the best content pieces available?

While knowing who the strongest players are is important, it’s also critical to know the top content assets and which are most successful in each market an organization serves. Data analytics allow teams to filter through libraries and see which content is resonating with prospects and target audiences. The data can track how often certain content pieces are used, which pieces most often appear in winning proposals and the best messages for varying verticals.

Using analytics, proposal and sales teams can also identify how frequently content has been refreshed to ensure any messages being used in the RFP process are relevant and rich. According to the recent Qvidian survey, respondents cited receiving content that is up to date as their top pain point, followed by getting content on time. With the help of proposal automation software, content writers ideally have more time to focus on developing and refining key messages—and with analytics in place, they’ll know which ones need more attention and which are working. In an effort to inform future processes, proposal and sales teams can also easily develop case studies and success stories based on previously used content.

Is this proposal worth the time and resources?

While every business wants to win more deals, it often doesn’t make sense to commit the resources to pursue every prospect. With a strong data analytics system in place, teams can easily determine if a proposal fits into their organization’s scope of work. They can also forecast the cost of responding to an RFP and compare that to the deal size to see if it’s worth pursuing. With access to insights like time spent on proposals, team sizes per proposal, the success of content pieces and win/loss rates (specific to industries, company sizes, etc.), it’s easy to determine which deals teams have the best shot at winning and which are likely not worth the time.

Proposal and sales teams that don’t analyze data derived from proposal automation software at the start of the RFP process are missing a huge opportunity. The time to start is now, and they can do so by looking at how teams and content are performing. That way, when the next RFP is placed in their hands, they’ll know their chances of winning and how to put together the strongest bid, creating a more efficient – and valuable – process overall.

Jeffrey Weil is general manager of Upland Qvidian.

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