Decision Intelligence in 2023: Prepare for These 10 AI & Machine Learning Milestones

As the new year begins, our industry experts present their predictions for 2023. Here are the opportunities and challenges facing a range of industries and business functions – and how technology will impact a company’s ability to succeed in a dynamic environment.

In 2023, the Promise of Decision Intelligence Becomes Clear

Ruan Van Vuuren

For the past two years, Decision Intelligence has been a trending topic. This year, we’ll see an awakening around this technology as more companies and industries realize the benefits of digitizing, augmenting, and automating decision-making.

We’ve historically seen an uptake of these capabilities across various industries, including pharmaceutical manufacturers, CPG, oil & gas, and manufacturing. More recently, we have also seen an increase in interest and uptake from telecommunications, automotive, airlines, mining, and wholesale/retail, among others.

The benefits of Decision Intelligence are clear in any industry that requires agile and resilient decision-making.

For example, in the telecom industry, the use cases for consumer business are apparent. For the networks and maintenance business, there’s a need to improve the return on assets by rebalancing work crews, equipment, and inventory of replacement parts across a complex network to support Infrastructure rollouts and maintenance of existing infrastructure.

We also see much interest among telcos in optimizing logistics and managing supplier risk. Some of the companies we are speaking with express concerns about the constant replanning required due to materials and parts shortages, and rescheduling of field crews and equipment. People are simply not able to cope with the volume and complexity of decisions.

In the airline industry, Decision Intelligence can make dynamic crew scheduling decisions in real time – tracking available flight crews’ current locations, ensuring they’ve met the legal requirements for rest and are positioned with the equipment and other resources needed for each flight take-off as scheduled. When weather, illness, or other factors impact crew scheduling, Decision Intelligence can automate the process of moving resources more quickly than human teams can, helping avoid a cascade effect of canceled flights and additional disruptions.

When discussing the future of Decision Intelligence, you have to consider the impact of a potential global recession and the role Decision Intelligence can play in mitigating risks. A recession can serve as a "reset" button. The companies that thrived after the 2008 recession and the 2018 Brexit recession were the companies that used the opportunity to reinvent themselves.

There are opportunities for bold, forward-thinking leaders to execute a true digital transformation of decision making without “ripping and replacing” their current technology stack by adopting a Decision Intelligence platform and forging a solid partnership to guide the process.

The Democratization of AI and Machine Learning

Lalitha Sundaramurthy

We are now seeing an increased awareness and realization that artificial intelligence and machine learning initiatives shouldn’t remain as standalone projects or experiments. AI and ML are demonstrating real value as they are operationalized within the company’s day-to-day business operations, and especially when they are leveraged to improve decision making.

Our recent study with BCG revealed that, in spite of significant investments, companies to date have not yet realized the potential of AI-managed supply chains. The study found that the root cause lies not with the technology, but with how and where companies have been applying it. Many companies have focused on AI for analytics and prediction, but have yet to pursue the more valuable application of AI to make recurring decisions by recognizing patterns within data that humans cannot see.

As more companies realize this potential, the demand for intelligence within business applications is going to skyrocket. The ability to meet this demand will become even more challenging than it is today. In 2023, this demand will lead to increased democratization of AI and ML, and a surge in collaboration among business users, application developers, data scientists, and data engineers in creating AI-powered applications – along with a realization that automated decision making is a new source of competitive advantage.

Decision Intelligence Transforms the Future of Work

Shariq Mansoor

People are very good at strategic thinking, but not as good at avoiding biases and dealing with high volumes of decisions that must be made. Today, technology allows teams to make better decisions at the point of impact, while automating many of the repetitive or routine decisions that take much of their time. These capabilities will change the workplace experience, and this year we’ll see an increased awareness of how technology can improve both the quality of work and employees’ level of satisfaction in the work they do.

Decision Intelligence has emerged as a category because we can no longer deal with the number of decisions we must make from day to day. In the past, technologies such as RPA and transaction automation helped at a lower level to ease the pain of some point business tasks. However, the current shortage of decision making ability comes at the same time that technology has evolved beyond simple transactional automation of a business process. Today, AI is capable of understanding the business, recommending a decision, acting to execute it, and learning to improve the quality of future decisions. This ability to digitize, augment, and automate business decisions is an inflection point.

Digitized decision making helps companies manage change by capturing the knowledge and historical decisions made by experienced leaders in procurement, supply chain, and elsewhere throughout the enterprise. These tools not only capture knowledge so that it isn’t lost due to employee turnover – they also contribute to employee empowerment and retention.

We will look back at this era as the inflection point in how companies make decisions, and how teams strategize and collaborate. While the underlying planning tools, ERP, and other technologies may be the same, the companies that have digitized decision making will be positioned for success.

Up to this point, there has been no structured platform for maintaining institutional knowledge. With Decision Intelligence, when faced with the next Great Resignation or other fundamental change in how we work, companies will be prepared with the combined knowledge of their best decision makers – as well as a work environment that fosters collaboration, creativity, and strategic thinking.

A Sustainable Agenda is a Must-Have, Not a “Nice to Have”

Alison Crawford

Sustainability and sustainable business practices were seen as nice to have or marketing led attempts to influence markets. This equated to efforts being well-funded PR campaigns rather than truly impactful climate saving efforts. The outcomes of this lack of action have become more apparent in the wake of more intense storms, droughts, and fires.

In 2023, there will be a shift towards action and a data-led approach to sustainable business practices. Governments are cracking down on greenwashing, and additional regulations will be enforced with increasing penalties. Because of this, companies will invest in technologies that not only track metrics around areas like carbon outputs so they can report on them with transparency, but will proactively identify areas for improvement to reduce waste, improve logistics, and reduce waste. This will foster an environment for agile and niche technology providers to deliver some truly transformative solutions that will impact the sustainability agenda significantly.

Digitized Decision Making Transforms Procurement

Jennifer Chaplain

Imagine being able to instantly respond and mitigate sourcing and procurement issues in your supply chain, on the fly, quickly and more accurately. For example, having the ability to compensate for unexpected shortages in key parts – and not only keep assembly lines running, but gain the confidence the best decision has been made for your product lines, preventing delays and impacts to bottom lines and customer service.

Artificial intelligence, machine learning, and automation technologies will provide the fast, real-time data insights required to replan production and customer allocation on the fly and advise transportation providers, suppliers, and customers of changes required – enabling dynamic response to ever-changing conditions.

As digital technology continues to evolve procurement operations, and as enterprises determine the best balance between teams and automation, we will see intelligent, augmented, and automated decision making emerge as a critical capability – alongside the need for a complete, digital memory of decisions across end-to-end processes.

Starting now and over the next two to five years, procurement teams will move from an operational environment that focuses on processes and transactional recording systems – often only showing us “what” happened – to a world where organizations have an “always-on” memory of the decisions made, and why, along with the options or recommendations that were available. This will provide a digital record that can be analyzed to inform strategy going forward – and will be specifically critical when businesses have to justify the social and environmental impacts of their procurement decisions.

Supply Chain Planning Adapts to Ongoing Challenges

Michele Vismara

As 2023 begins, the supply chain challenges we’ve seen in the past year will continue, particularly around (A) the ability to reliably source materials, and (B) the cost and availability of energy.

These concerns will be further complicated by inflation. From a supply chain standpoint, there will be impacts on the supply side as the cost elements of manufacturing, transportation, and sourcing go up. Companies need to be able to understand and respond to these changes. The ability to factor inflation into a planning solution is not just a matter of business flexibility, but a matter of technology flexibility – one that Decision Intelligence helps address.

For example, consider the questions that must be answered around pricing decisions: How will companies react to an increase in cost? What’s the elasticity of demand to price variations? Have our clients already increased prices in the past, and if they cannot do so again, what other actions can they take? These questions are particularly important in fast moving consumer goods and electronics, with perhaps less impact in pharmaceuticals where there is less flexibility.

The current recession also further highlights the need to build flexibility and agility into supply chains – to avoid risks when possible, but also to manage them whenever they appear. Decision Intelligence leverages the computational power of machines and AI to make decisions quickly, and at scale.

Manufacturing: The Year of Connected SCADA

Matthew Bunce

This year, technology opens up new opportunities to integrate data sources with the shop floor for better product lifecycle planning. Manufacturers’ supervisory control and data acquisition (SCADA) systems gather real-time data in order to manage equipment and operations. Today, those systems can be further connected to planning systems – but Decision Intelligence offers an additional opportunity for visibility by directly connecting manufacturing operations with research and development (R&D) and demand data.

The benefits of this connectivity are clear for consumer goods manufacturers. Not only do consumers have many retail channels to choose from, but there are more product options and brand extensions than before, making demand difficult to predict. With Decision Intelligence, plant managers receive CRM and point-of-sale data in real time. When data science models are applied to this data, planners can not only sense demand more quickly and granularly – they can quickly factor those signals into more intelligent manufacturing decisions.

This connection between demand and the shop floor can also benefit pharmaceutical, electronics, and automotive manufacturing, among other industries. For example, manufacturers of wiring harnesses may provide similar products for different models of consumer appliances. It’s easy to change a wiring harness design, but it’s difficult to know which variant will be in greatest demand among the many different brands and models that must be built. Decision intelligence makes it easier to determine demand and shift manufacturing resources more quickly.

Similarly, tighter integration between R&D and manufacturing will enable better product lifecycle planning. R&D data sources, from PLM systems to simulation systems, deliver data that’s critical to designing and manufacturing products. However, this data took a great deal of time and manual effort to feed over to manufacturing. With Decision Intelligence, instead of relying on manual inputs from R&D engineers, the data from simulations is now readily available. Decision intelligence will help companies access and analyze this information by delivering augmented recommendations so that they can better match demand cycles.

CPG’s Challenge in 2023: Reducing the Impact of Unknowns

Naveen Kumar

Given the impacts of inflation, a turbulent job market, and ongoing concerns about availability of raw materials, consumer packaged goods companies enter the year with a great deal of uncertainty – and the potential for many decisions to be based on assumptions.

From a decision-making perspective, those who are able to reduce the number of these unknowns through better information and analysis will be better situated to know the true impacts of inflation, changing demand profiles, and changing consumer spending patterns. They will use that information to reduce the inherent risks of consumer promotions, new product introductions or channel expansions in 2023.

As companies make course corrections this year, particularly around short-term delivery businesses, I expect that D2C will continue to be the most rapidly-growing channel though we can expect to see a bit more pragmatism in the new year which has seen some over-indexing on growth recently . The challenge for CPG companies will be execution – ensuring this business model is sustainable – which in turn will require changes to supply-chain design and the agility in everyday execution to adapt to changing scenarios.

This is where CPG companies will benefit most from an automation layer. With limited availability of decision making time, companies will need to accelerate end to end supply chain decisions based on multiple criteria: revenue maximization, strategic customer relationships, availability of materials, and more. These decisions may be made not just from week to week, but from day to day, requiring companies to invest in a Decision Intelligence platform that gives them a greater level of visibility and agility, without replacing their existing solutions.

The first quarter of the calendar year 2023 will be crucial as companies face more unknowns than in previous years. It has been difficult to make predictions two or three months out, much less a year in advance. Faced with less time to react to changes, technology will be crucial – allowing companies to combine views of internal and external factors to understand the current situation and make the best decision at the moment of impact.

Pharmaceutical Firms Achieve Greater Agility

Michael Späth

Across many large, R&D-driven pharma companies there is a drive to develop blockbuster drug products. These products typically have 10- to 15-year development cycles from inception to commercial product, along with significant overhead costs. Innovation is happening in the biotechnology space, with many industry leaders acquiring young, innovative companies with the goal of leveraging the full value chain, from sourcing to manufacture and delivery.

Inflation is impacting the pharmaceutical industry differently in different geographics. In the US where there is more freedom to price, the impact of inflation is carried over more directly into the healthcare system, while in the EU there is both more restrictive pricing and more concern about public pushback and resentment which will impact pricing decisions in 2023.

Meanwhile, despite Covid-19 continuing to impact millions worldwide, companies can expect to see the contribution of coronavirus-related sales diminishing – particularly in areas involving healthcare equipment and consumables which are susceptible to an ongoing bullwhip effect from past inflated demand.

Finally, healthcare companies have struggled to fill key positions in recent months – a trend that has impacted firms across lines of business from manufacturing to management. This challenge, along with the current recession, has led companies to focus on core workforce and find opportunities to outsource non-core capabilities to service providers when possible.

Against all these factors, agility is a key source of competitive advantage, with companies seeking every opportunity to reduce the time they spend making decisions. Decision Intelligence is poised to address these decision-making challenges – from managing clinical trials, to integrating the data and technology stacks of acquired firms, to capturing institutional knowledge and augmenting and automating decisions at the point of impact.

Chemical Industry trends in 2023

Neil Fulkes

Global economic uncertainty will shape the challenges faced by the chemicals industry in 2023. Economic indicators, such as inflation in raw material costs, significant volatility of energy prices, and disruption of trading patterns, will mean challenging times are ahead for business leaders. However, there are a number of strategic initiatives that organizations can take to help overcome these challenges and position themselves for future agility and growth.

The first of these initiatives will see a focus on supply chain redesign. To succeed, supply chain leaders must find a balance between agility, efficiency, and resilience. Cost will continue to remain a concern; however, ongoing supply chain volatility will mean that organizations will need to build resilience to withstand unexpected shocks. Technology transformation is likely to provide the solution to this challenge.

This leads to the second initiative, which is digital transformation and the use of emerging technologies to drive value chain improvements. Over the last decade, many large producers have invested in their digital core to modernize their technology landscape, and now they need to monetize that investment. However, in order to realize this benefit, organizations need to continue to evolve by striving to improve their visibility and agility of decision making across the end-to-end value chain.

Across both of these initiatives, Decision Intelligence is well-positioned to help chemical companies address the challenges that they will face in 2023. From predicting and managing supplier risk, to delivering sustainability goals, to achieving cost targets while maintaining service levels, agility and speed of decision making at scale will be critical to success and competitive advantage.

Watch our on-demand webinar, “The Top 10 Predictions for 2023 from Aera,” for a full discussion of how these trends will impact your business this year and beyond.

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