The Power of Artificial Intelligence to Anticipate the Unpredictable.

Before the pandemic, many companies focused on efficiency and lean supply chain models, prioritizing inventory reduction and ensuring that products were available just in time to meet customer demand. This approach aimed to lower costs and maximize operational efficiency, leaving little room to handle unforeseen disruptions. Operations centered on waste reduction and efficiency improvement, seeking to deliver the greatest value to customers through effective resource use. Operations managers continuously analyzed tasks, processes, and staff to eliminate non-essential activities and ensure smooth communication at every stage of the workflow. Digital transformation played a crucial role in this optimization, centralizing data and increasing visibility, which allowed leaders to have greater control over operations.

However, the upheaval caused by the COVID-19 pandemic and international instability in recent years led to a drastic shift in this approach. These meticulously optimized systems, which had undergone iterations of minimal changes to operate as efficiently as possible, suddenly faced a wave of unpredictable problems. Lockdowns worldwide resulted in shortages of certain materials or components, quarantine times caused delays in transportation across borders, and changes in people's daily lives disrupted the demand curve. Additionally, the increase in remote work forced adaptations in internal processes, necessitating the implementation of new communication and collaboration methods.

The goal of optimization was no longer a priority, as the gains from this approach became irrelevant in the face of significant losses. The focus shifted towards operational resilience. Organizations that managed to thrive were those capable of withstanding, adapting to, and recovering from disruptive events. Practically, this means having flexible logistics routes that can adjust to geopolitical situations, managing multiple sources nimbly, and implementing tactical contingency plans. Organizations that successfully executed these structural changes managed to avoid order cancellations and maintain revenue stability.

The pandemic left an important message: time spent solving predictable challenges limits resources for facing the unpredictable. Since the pandemic, a certain degree of normalization has been observed in industries, although the footprint of these extreme events remains present. Operations managers, while once again seeking small improvements based on lean supply chains, are aware of the possibility of chaos from uncontrollable events. Thus arises the dilemma of how much time to dedicate to daily challenges and how much to foresee the bigger picture. Resource scarcity entails a trade-off between efficiency and resilience, both essential for organizational success.

The solution lies in automating responses to predictable challenges. Technological advancements are enabling organizations to automate increasingly complex tasks. Activities that once required the manual intervention of employees can now be performed by machines. This automation not only reduces the margin for human error but also allows workers to focus on more complex and fulfilling tasks, leaving routine tasks to artificial intelligence or machine learning models.

In the context of the trade-off between efficiency and resilience, automation can address predictable challenges, thereby maximizing operational efficiency and reducing waste. Artificial intelligence can manage processes, such as sales and operations planning (S&OP), coordinating various sectors of the business to meet customer demand with the appropriate level of supply. Demand forecast accuracy reports (DFA) can also be automated, alleviating the burden on team members.

AI chatbots can facilitate communication with stakeholders and improve information flow both internally and externally. These models can analyze large amounts of data, gathering useful information for decision-making. For example, a chatbot could immediately provide stock availability and plans to partners and customers, as well as to the sales team, reducing the need for manual research and email exchanges.

However, automation operates under the premise of regular and uninterrupted processes, meaning it is not prepared to handle irregular events, such as the pandemic. Material shortages, prolonged transportation times, and demand instability inevitably affect ecosystems. This is where the human element comes into play.

Technologies such as artificial intelligence and machine learning allow personnel to anticipate unforeseen challenges and use these predictions to create effective solutions. The number of possible scenarios requires combining complex models with human judgment and creativity in order to formulate reactive strategies, enabling navigation through large-scale obstacles. This may involve developing relationships with alternative suppliers, stockpiling key components, or working with customers to suggest a staggered delivery schedule in times of crisis.

Instability is a constant reality, and the modern world will always present us with challenges that are difficult to foresee. The trade-off between efficiency and resilience is not a topic we will see disappear soon. Organizations must innovate and adapt, using automation to address daily optimization challenges, allowing employees to focus on anticipating the unpredictable. Thus, when the next obstacle arises, we will be prepared.