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Unlocking value potential from GenAI in Oil & Gas

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GenAI Oil & Gas

The tender process is often resource-intensive and tedious, plagued by inefficiencies and a lack of focus on commercial terms. This issue is especially pronounced in global industries like oil & gas, where tender complexity has increased significantly. The solution? Generative AI. Discover how Gen AI is revolutionizing the supply sector by accelerating tender performance.

The oil and gas industry has a powerful tool at its disposal: Generative AI (Gen AI), with its immense potential to accelerate tender performance and unlock value creation levers across the commercial agenda.

By harnessing Gen AI technology, the oil and gas industry can improve tender success rates by automating repetitive and labor-intensive activities and reducing human errors. This shift enables companies to focus on high-impact aspects of the bidding process and also expand to a global platform. Our project experience serves as a testament to this.

High-stakes oil and gas tender complexities

In a recent project, we supported an oil and gas well intervention company on a critical bid for a major regional player in Northern Europe. The tender, valued at nearly €70 million, was pivotal for our client and their competitors. The bid, anticipated through local relationships and channels, involved a tender document exceeding 100 pages with highly technical descriptions. The tender team, consisting of about 30 people, spent nearly three weeks on the technical specifications, leaving limited time to focus on the commercial aspects. There was a general feeling that commercial decisions were rushed and based on gut instinct due to the lack of time before submission.

Given that oil and gas intervention services are relatively uniform worldwide, many tenders are global in scope. However, they are often written in local languages, structures, and terminologies, making them resource-intensive to understand and review. Consequently, many service companies are disqualified from tendering due to the complexity of the bid and the RfQ (Request for Quotation) process.

One of the challenges for our client was the lack of uniformity in procurement response sheets – each submission looked different from one large oil company to the next. Shell’s tender templates look quite different to Conoco’s – even when they are tendering for the same service is tendered for. It often took a long time to simply understand how the form should be filled out.

In the offshore supply sector, tender processes and responses are how many companies initiate their sales processes. Requests for proposals often consist of hundreds of pages of PDFs that need to be meticulously reviewed. This process is long and tedious, frustrating both the sales and bidding teams. Experienced personnel are required to navigate these complexities, but human involvement increases the risk of errors and may lead to poorly matched proposals.

This is one area where Gen AI can add value.

The role of Generative AI in the RfQ process

Gen AI can significantly streamline the RfQ process by extracting relevant information from incoming RfQs and matching the correct input into any RfQ response sheet. Advanced applications can service smaller RfQs autonomously. This is particularly advantageous as this allows teams to focus their expertise on commercial elements of the bid.

Meanwhile larger tenders will also benefit as they undergo efficient review facilitated by this technology. The RfQs will still require human review but without the need for the most time-consuming work beforehand.

Commercial impact points

It’s reasonably straightforward. In commercial applications, Gen AI can impact four key performance indicators (KPIs):

  • number of leads
  • win rates
  • average order size
  • length of the sales cycle

Even small improvements in these metrics, like 5 percent (in each), can collectively result in a 21.8 percent rise in revenues. This demonstrates that incremental efficiency gains can significantly impact the topline without needing a complete overhaul of sales and bidding processes.

AI’s transformative potential

AI can dramatically improve tendering processes by automating the initial review of tender documents. Upon receiving an RfQ, the AI reviews the documents, extracts product and service specifications, and matches them to existing data in the company's systems. This automation includes the ability to understand complex terms and conditions, such as for Incoterms, which can be challenging and time-consuming even for experienced bidding teams.

The AI then presents a summarized output, best suited for review. This can be a draft of a filled-out tender response document. This allows the bidding and sales team to focus on high-value tasks like fine-tuning the proposal, preparing and planning the potential negotiation, and engaging with the customer. This shift from manual, time-intensive tasks to value-generating activities significantly increases efficiency.

Case study: Improving tender response efficiency

In our project, the introduction of Gen AI led to a 30-40 percent increase in efficiency per full-time equivalent (FTE). Win rates improved as the sales team could focus on selling rather than getting bogged down by technical details. Previously, during peak times, the quality of tender submissions often deteriorated, or proposals were ignored due to the team's inability to handle the volume. With AI, the volume of completed proposals increased, eliminating this critical bottleneck.

Broader applications and future potential

Beyond tender responses, Gen AI can also enhance customer interactions through chatbots and other automated services, demonstrating its versatility. By leveraging AI to handle routine tasks and data processing, companies can redirect human efforts toward strategic and creative endeavors, driving overall business growth. Leveraging this new technology correctly is key to improving the commercial operations. As companies transition from “using digital tools” to “being digitally enabled”, they make a critical jump forward to what will be the new status quo in the oil and gas industry.

In conclusion, the strategic implementation of Gen AI in the tendering process can transform the upstream sector. By automating labor-intensive tasks, reducing human error, and allowing teams to focus on high-impact activities, companies can significantly improve their efficiency and competitiveness in the market.

Interested to learn how you can unlock value potential from Gen AI? Contact us to discuss the path forward for your business.

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