Although every revolution, such as the arrival of AI, involves a complex process in its assimilation and implementation, at this moment it begins to seem obvious to insist on the fact that any logistics department or company in the sector with a minimum of complexity and growth vision, you must seriously review your entire strategy around the need to explore and evaluate how Artificial Intelligence and all the associated advanced data analytics techniques are going to impact your processes and your business model. business .

Despite the existence of certain extreme currents of opinion, the majority of researchers and professionals in fields related to Artificial Intelligence agree on a normalized, gradual and less extreme vision of this exciting change that we are experiencing.

Technology applied to Logistics: transformative capacity

Being aware of its importance and the transformative capacity of the software development services that are being developed, we begin to understand the disruption that these changes are going to entail - and are already entailing - in very different areas and activities of the economy and society. And specifically, in the world of logistics due to its increasing complexity and the level of demand that consumers impose as they are accustomed to buying and enjoying the product in 24 hours (or less) without added costs that make the product more expensive. 

Not all organizations are knowing or being able to react with the same agility to this evident new paradigm that we are beginning to glimpse.

Notwithstanding the above, all the cases related to the implementation of these technologies indicate that not all organizations are knowing or being able to react with the same agility and the same vision to this evident new paradigm that we are beginning to glimpse.

Keys that make the difference 

Thanks to our experience advising companies in the sector and logistics departments of large companies on the best strategies, applying these disruptive technologies at their different levels of long-distance, medium-distance and capillary distribution - as well as in their intra-logistics challenges to increase the profitability, efficiency and sustainability of its critical processes -, we could openly share some keys that we believe can make the difference between the success and failure of these initiatives: 

• The business in the center Custom software development services are a multiplying factor that must always be subordinated to the business. Advanced digitalization, applying techniques such as Artificial Intelligence and Operational Research, must be based on a clear definition of the business strategy, and on a deep analysis and knowledge of the value chain and the associated critical processes.

• Take care of the raw material - the data - as what they are , one of the greatest assets of the organization
  
  Properly govern our organization's data generation, custody and aggregation capacity as a lever for enabling and accelerating the construction of value from advanced analytics.

• Build an internal digital culture with clear sponsorship from senior management
  
  With the greatest corporate alignment and prioritizing “quick-win” projects that allow us to iteratively grow in complexity and added value; with a government model that scales on consolidated values; and about an informed and aligned organization.
  Specifically, and for logistical challenges, multiply the value that Artificial Intelligence already brings us by hybridizing it and using it as input for Operational Research (process optimization).
  With applications from which organizations are being transformed and creating a differential competitive advantage. They are techniques that every day demonstrate to us the synergy of extremely high combined value that has the potential to impact a multitude of complex logistical challenges.

• Use case versus business case
  
  These types of initiatives, where innovation and everything that it implies in itself take a decisive role, we cannot manage them under classic evaluation models based on a business case, because in most cases, we do not know the final net value of their implantation. The launch of innovation processes by custom software development companies  in our organizations, with transformation potentials as high as those that Artificial Intelligence or Operational Research can provide us, must be more flexible and assume the iterative nature of the innovation process. Therefore, in many cases a bolder management capacity is required, which understands and allows the use case to lead, and the iteratively increasing business value to end up defining the business case.

• The ethical aspects of the technology developed and implemented
  Although, as always happens, the regulatory and legal aspects associated with technological developments are years behind their emergence, we must be fully aware and responsible for the transcendental importance of aspects such as auditability, explainability or traceability of Artificial Intelligence models. deployed, especially in those application scenarios in which a social impact is generated.