Every large-scale corporation in the industry domain is currently thinking about what possibilities generative AI can unlock for them. These organizations have an incredible amount of existing data, scattered across internal company databases, excel spreadsheets, emails, PDF documents, and more. When done right, this information can be leveraged into highly powerful applications that assist in transforming organizations.
When thinking about starting points, there’s no better place than under your own hood. Most industrial companies are home to vast amounts of data that can be used to build effective, internal applications that help streamline operations, reduce mundane tasks, and speed up processes that help make better informed decisions. Because of the complexity of manufacturing businesses, the opportunity to automate heavy, manual processes can make a massive difference.
In order to find just the right opportunity to go for, companies should assess the viability of an idea alongside its ROI hypothesis. This means looking at the scale of impact, associated development costs, integration into existing workflows, and the time required to realize real value.
To help you get started, we identified five ways to start applying generative AI across your business.
1. Simplifying customer debugging and support
Imagine a scenario where you purchase sophisticated factory equipment or machines to run your logistics operations, and unexpectedly run into unforeseen technical glitches. Traditionally, this would require a call to first-line support or a dealer, likely being passed to back-line, all while leading to lengthy downtimes and therefore significant costs.
Imagine if in the scenario described above, rather than calling various customer support lines, sifting through support manuals, or escalating issues through a support ticketing system, you could bypass this convoluted process and find solutions independently? GenAI has the ability to transform these customer service situations into streamlined, and even empowering, experiences for clients and their own professionals. By leveraging a chatbot or virtual assistant powered by GenAI, customers can access a vast repository of the company’s collective knowledge and past resolutions. This system would enable users to describe their problems in natural language and receive the most likely solutions by parsing through manuals, videos, support tickets, and other sources of company knowledge.
This approach not only empowers customers to resolve the majority of issues on their own, but also significantly reduces the burden on support teams – allowing expert staff to focus on more complex problems that require their specialized attention. Integrating GenAI into customer debugging and support minimizes equipment downtime, cutting down costly delays and frustrations associated with traditional support channels. When every minute of machine inactivity translates to financial loss, providing customers with immediate, effective troubleshooting tools can make all the difference.
2. Optimizing technical sales workflows
Technical sales, particularly in many industrial companies, is usually never just cut and dried. Intricacies in language and specific technical requirements often make it a challenge for both sales and technical professionals to pin down the scope of a client’s needs.
For example, ABB’s typical sales flow involves receiving Requests for Engagement (RFEs) through various formats such as email, PDFs, Excel files, and text documents. Sales professionals are then tasked with reading through potentially hundreds of pages of documentation. The sales team makes notes on services such as Microsoft World, or by highlighting important sections directly on printed documents, attempting to get a comprehensive understanding of the client’s explicit and implicit requirements. From there, the sales professionals might have a conversation with the client to clarify details or discuss possible deviations from the initial requirements, maybe due to regulatory or product considerations. Despite a highly customizable range of products, there may still be a need to adjust based on a given client’s individual set of demands.
Generative AI is changing the nature of these types of processes. In the context of ABB, tools built using GenAI help them sift through, summarize, and extract vast amounts of baseline information about a customer’s needs and requirements. This facilitates deeper understanding and enables more informed decision making. Sales teams can quickly determine the viability of making an offer or dedicating resources to a project based on a comprehensive overview provided by the GenAI tool. This technology streamlines the very laborious process of RFEs and RFQs, saving time, money, and sales teams’ headaches.
3. Supercharging product search and comparison
Getting the right information in front of the customer efficiently helps facilitate purchasing decisions. Historically, this has been done through a combination of web pages, catalogs, configurators, and sales decks, which require the customer to take a proactive approach in filtering through to the relevant information on their own.
GenAI unlocks new possibilities to rethink what these workflows could look like. For example, by training a conversational bot on all of your sales material, you can make this experience interactive. Rather than scrolling across countless, extensive static material, customers can ask detailed questions, compare multiple products at once, and evaluate pros and cons. If your products have public reviews, marketing materials, or other news or announcements, this configurator could help surface reviews and provide in-depth analysis on expert recommendations as well.
Supercharging product search and comparison tools is also beneficial in the hands of dealers. Rather than having clients go through messy material banks or catalogues, dealers can rely on these AI powered tools in discussions with clients. The same goes for the client’s professionals, too.
4. Automating customer order management
Customer order management in heavy industry usually means processing orders filled with diverse materials, solutions and services, ranging from PDFs and Excel spreadsheets to custom specifications over email. The complexity increases when orders include configurable or custom-made products with specific requirements scattered across various documentation formats.
GenAI can streamline order management by intelligently identifying, parsing and organizing data from multiple sources into a system with coherent order information. It’s able to recognize and extract the necessary information, regardless of format, making sure that every customer specification is validated and accurately incorporated into the processed order. This automated process not only speeds up operations but also dramatically reduces human error.
GenAI can help enhance order accuracy by identifying inconsistencies or missing details. This proactive approach prevents mistakes and delays, improving customer satisfaction through precise and efficient order fulfillment. Furthermore, GenAI can help to identify at an early stage if there is no matching offering to the order, saving time from unnecessary order processing.
In certain cases GenAI can suggest options that deviate from the original order but still match with the customer's underlying business need or use case. This results in more sales opportunities, but the solution can also be a useful tool for new training and staffing models, because such in depth knowledge often requires long-term industry experience. Now the valuable experience can be used to train GenAI to ensure that the often undocumented know-how is fully utilized and never lost.
5. Streamlining business reporting
Business reporting in large-scale corporations is an all-around complex challenge. The process of compiling and extracting information from internal systems, emails, and other communication channels has historically been near-impossible in providing a wholly comprehensive overview.
Corporations that serve hundreds of markets have to navigate through an overwhelming amount of data that is often monitored and reported individually in each country. This results in key business related information getting buried in email chains. It’s not uncommon for explanatory information, such as issues affecting profit margins or other critical financial details, to exist in a single leadership team’s private exchange of messaging. This makes the task of assembling a truly comprehensive overview of a company’s business performance a very difficult one.
GenAI has the potential to have transformative effects when it comes to your reporting. With GenAI, you can summarize vast amounts of data, enabling financial teams to ask nuanced questions about compiled reports, such as, “Why hasn’t there been similar growth in the LATAM market as we’ve seen in EMEA lately?”. GenAI can incorporate insights from public materials on the web, including trends and implications across various industries, enriching business reporting with further context and depth. This can be done, for example, by summarizing competition highlights within a certain market or by digging out financial oversights for key customers.
These types of capabilities not only streamline the reporting process, but also help enhance the quality of insights derived from the data.
Download our white paper to learn more about how industrial companies can leverage data for internal productivity.
contact
Let's build together!
