The manufacturing industry is facing incredible pressure from every side: customers, suppliers, and competitors. The solution to dealing with all of these factors may well lie in the ability to harness the potential of emerging technologies, such as artificial intelligence (AI).
Manufacturing businesses today operate in an increasingly complex landscape — whether it’s managing global supply and demand, the impact of rapidly changing customer expectations, changes in taxes, disruptive technology trends, or changes to regulations and standards.
Not only must manufacturers adapt to changes in this complex landscape, but they must also do so quickly to remain competitive and avoid losing market share. Yet as the business landscape continues to evolve, driven by changes in all these factors, manufacturers must constantly consider and balance a huge range of variables to their business model. Ultimately their ability to juggle these variables can dramatically affect their profitability, their market share, and increasingly, their ability to survive.
Simply understanding the interactions between competitors, suppliers, global markets, customers, and business models is a task that is already outstripping traditional management methods. There is simply too much complexity and too much data for your average human to process and understand. Therefore, machine learning-based technologies are emerging as one way that businesses can ensure they stay on top of changes quickly enough to protect and grow revenue.
One of the most powerful capabilities of machine learning-based technologies such as AI, is that they can consume and evaluate very large quantities of data in a way that humans cannot. This allows good AI engines to seek out patterns in huge amounts of information, and having found those patterns, proactively offer advice and guidance.
Simply put, AI can look at more data, and do so more quickly and more thoroughly than a human. AI tools should also learn as time goes by, improving their ability to offer better and better insights into the key indicators business need to thrive. This capability is what puts AI right at the heart of solving the very kinds of complex problems that we see global businesses facing today.
Manufacturing and the Increasingly Digital Landscape
While traditional selling through person-to-person relationships continue to be important, the shift to online commerce has opened the doors to directly connecting with customers. If businesses can get it right, there is an opportunity to translate closer customer relationships into commanding a higher price by delivering greater value to a customer, while also reducing overhead and streamlining the customer’s buying experience. However, the shift to digital commerce also introduces a new set of complexities in the industry that many organizations haven’t before faced.
When customers are no longer speaking directly to a sales representative and start going through ecommerce channels instead, many organizations worry that they will lose the ability to identify changes in buying behavior, as well as miss opportunities and threats in the market.
Yet AI technologies can play a critical role in enabling a successful move to ecommerce, by alerting manufacturers to shifts in the market, allowing businesses to figure out what works and what doesn’t work by looking at what’s successful and what’s failing. Further, manufacturers can also better establish insight into customer needs and create valuable insights through a deeper understanding of buyer behavior — the kind of insight that only analysis of huge volumes of interactions, both good and bad, can deliver.
This capacity to consume large amounts of data, customer transactions and broader market activity, enable AI-based business systems to respond quickly and effectively to changes at every step, from changes in tariffs and the subsequent potential implications on supply chain, to a shift in buyer preferences and behavior. This helps manufacturers more clearly understand the true costs, and value, of their products, so that they can set the right price at the right time for each customer.
The opportunity with AI and machine learning is enormous — it can reshape the way businesses interact with the market, increase value and strengthen a business’ overall bottom line.
Using AI to Overcome Pricing Challenges
The constant pressure to commoditize products makes it difficult to protect price points especially when manufacturers aren’t clear on what really drives customer behavior. To respond effectively, manufacturers must process huge volumes of transactional information, extract meaningful insight, and then make smarter decisions. Quickly.
Additionally, changing economic variables leave less room for error in the ever-evolving manufacturing environment. It’s harder and harder to control for fluctuating material prices and demand, but manufacturers must respond in as short a time as possible.
Traditionally, companies may have evaluated their pricing every few months, or even annually. Now there is a move to evaluate pricing much more rapidly, sometimes in near real-time. This kind of agility can only be delivered through consuming and analyzing large volumes of data and then responding across entire portfolios of products.
The advantage of AI-based analysis is that it can provide recommendations-based on a huge number of data points very quickly.
For example, if a business has to change the price of an end product, what are the likely impacts to revenue and profitability? Where are the opportunities to command a premium price, and which customers are highly price sensitive? Businesses that can understand their customer’s preferences most fully have a measurable edge over their less-agile competitors.
Tools utilizing machine learning and AI can work quickly and deliver prescriptive insights. While sales representatives can’t always spot patterns, an AI can see something a human might miss and even detect an aggregate shift in customer behavior. This ability to look across very large amounts of information in order to extract real insight can be transformational to the way businesses are run. Businesses that utilize AI tools to solve real operational problems and deliver strategic guidance are already showing measurable and significant growth in market share and revenue.
Benefits to Using Ai in Overall Business Operations
AI-based analyses are a powerful competitive weapon. As markets undergo more rapid changes, and as the impact of technology disruptors become more deeply felt, the competitive differentiation of AI becomes all the more profound.
Companies are putting AI-based technologies right at the heart of how they run their business. For example, the airline industry took such an approach years ago when it began using machine-learning analytics to manage the complexities of fares and seat availability.
That same approach has evolved over time to now enable businesses of all kinds to utilize dynamic, AI-based analytics to respond very rapidly to changes in their markets and answer questions such as, “How do I best remain profitable if my supply-side costs change?” and, “How do I operate in the face of a natural disaster such as a hurricane?”
AI can also answer more forward-looking questions like “Where else should I be looking for market growth opportunities? How do I sell more to customers with which I might not yet be fully engaged?”
This is all part of addressing the challenges and opportunities of digitalization. Manufactures that successfully embrace the full opportunities of the shift to digital business are not just thinking reactively, they are actively reshaping how they interact with the whole market.
AI-based business technologies are not science fiction — they are real and have been employed successfully in manufacturing businesses for some time. They’re here today, and businesses that can adopt this approach sooner rather than later will be more resilient in the face of unexpected change and better able to respond to market opportunities. In the end, they will be smarter, faster, and more agile, and in the world of global competition and changing regulatory landscapes, that’s what defines a winner.
Geoff Webb is VP of Product Marketing at PROS.
