How To Automate The Bid Management Process With Artificial Intelligence

Artificial Intelligence (AI) has been at the forefront of saving businesses valuable time and resources for quite some time now. It has made revolutionary impacts and discoveries from maps and navigation, chatbots, text editors, digital assistants, facial recognition and more. Individuals and enterprises use these AI-powered systems every day, and the best part is that we are just getting started.

It is crucial to note that AI-powered technology should not threaten humans or make them fear losing their job. It should excite them. These solutions aim to improve one’s job, increase productivity and optimize current resources.

Businesses worldwide have varied goals and objectives but tend to share one consistent attribute: They want to make the most of their time and resources while stabilizing the cash flow of their business. Using artificial intelligence to automate the tedious journey of winning a contract can help bid managers save time and secure business for their enterprise, a “win-win” situation.

To highlight how AI can do this for your enterprise, we must look at three critical steps in the bid management process and address some initial concerns:

1. Research And Planning

Today, a typical tender process involves many different departments such as management, administration, R&D, operations certifications/audit experts, security and more. The bid process cannot truly begin until two critical questions are answered: Is your company a fit for this contract? Do you have the resources to meet the demand of this tender?

Answering these questions requires the bidding team to have large amounts of knowledge at their disposal. Perhaps, some of the most helpful information to a bid manager is older request for information (RFIs) and previously won request for proposals (RFPs), as this gives clear insight into what worked well in the past.

A data silo is a collection of isolated data that remains invisible to a large part of an organization. Hidden knowledge cannot be analyzed during the research phase of any process. The inability to extract data from data silos or different departments can lead to the loss of valuable time. Bid managers will spend hours searching for specific information they can’t reach or waiting for a colleague to send them this information.

Eliminating this “middleman” can be prominent to the bid’s success, and having an AI-based solution to extract much-needed data leads to increased information sharing and collaboration across departments.

2. Leveraging The Full Power Of Your Organization To Write A Winning Bid

Content generation is another area where AI can help. With machine learning capabilities such as natural language processing (NLP), solutions can find answers to questions by sorting through already existing amounts of information. NLP allows machines to understand the questions and help teams formulate accurate responses by accessing available data. Instead of combing through countless documents, answers are generated from high-quality knowledge within your enterprise’s systems.

As touched on, a significant part of writing a winning bid is learning from the past. Part one includes analyzing former RFI and RFP responses. What worked well? What did not? A successful bid must utilize knowledge from current knowledge bases, such as white papers, blogs, FAQs and any other documentation your business is using.

Competitive analysis can also provide details into best practices your competition uses in their tender process. Accessing this knowledge can benefit your team with new ideas and give you an edge when competing for a tender.

Gap analysis enables your enterprise to identify possible shortcomings in achieving business goals and targets. Are there any questions on a current tender you have never answered before, and are these showstoppers? Gap analysis can help you identify showstoppers and pinpoint why they might be.

3. Using Knowledge Carriers Properly And Tracking The Progress

Efficiently answering RFPs and finding out which ones are most likely to win is critical for company success.

Bid management teams must minimize processing time, but quality needs to be improved, an area where AI solutions can make an impact. If information from former RFPs and RFIs is available, the time of “company experts” can be saved. Knowledge experts are those whose time is most valuable and critical, so only using them when brand-new tasks arise is essential.

Like all projects, organization and the ability to track your steps are necessary. Large enterprises often have multiple tenders running at one time. AI-driven tools can give you a detailed overview of your activity in each ongoing bid, ensuring nothing goes undone. The slightest misstep could be the deciding factor of winning or losing a contract.

Expectations And Concerns For An AI-Driven Bid Solution

It is usual for concerns to be raised when beginning any technology solution, and the idea of automation can be scary for many businesses.

Companies often worry, for example, if they have enough data to generate proper responses to win bids. Suppose you don’t believe you have enough existing internal data. AI can formulate relevant answers, as long as all data sources are connected. The connection to third-party data sources is possible via data connectors with a handful of solutions available on the market.

Many business leaders also worry if AI will provide the best possible answer to a tender and if losing the human touch could be detrimental. The fact is, the human touch will never entirely leave the picture. When generating content for your organization, there are many aspects to consider: content optimization, competitive analysis, topic research, tone, grammar and more. AI is a tool to leverage and assist with suitable bid writing components. Bid writers can use AI and not feel the need to start from scratch on every new RFP and RFI.

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Original post: https://www.forbes.com/sites/forbestechcouncil/2021/12/27/how-to-automate-the-bid-management-process-with-artificial-intelligence/

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