From Challenge to Transformation – How Technology Applied to Logistics

From Challenge to Transformation – How Technology Applied to Logistics

Although any 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 vision of growth, you must seriously review your entire strategy around the need to explore and evaluate how Artificial Intelligence and all associated advanced data analytics techniques are going to impact your processes and your business model.

Despite certain extreme currents of opinion, most 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 technologies being developed, we are beginning to understand the disruption these changes are going to cause -and are already causing- in very different areas and activities of the economy and society. And specifically in the world of logistics, due to its growing complexity and the level of demand that consumers impose as they are used to buying and enjoying the product in 24 hours (or less) without added costs that make the product more expensive. 

Notwithstanding the preceding, all the cases related to implementing these technologies indicate that not all organizations know or can react with the same agility and vision before 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 different levels of long-distance transport, 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

Technology is a multiplying factor that must always be subordinated to the business. Advanced digitization, applying techniques such as Artificial Intelligence and Operations Research, must be based on a clear definition of the business strategy, deep analysis, and knowledge of the value chain and associated critical processes.

  1. Taking care of the raw material -data- for what it is, one of the organization’s greatest assets
  2. Properly govern our organization’s data generation, custody, and aggregation capacity as a lever for enabling and accelerating value creation from advanced analytics.

Build an internal digital culture with clear sponsorship from senior management

With the most significant corporate alignment and prioritizing “quick-win” projects that allow us to grow iteratively 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, multiplying the value that Artificial Intelligence already provides us by hybridizing it and using it as input for Operational Research (process optimization).

With applications from which organizations are being transformed, creating a differential competitive advantage. These are techniques that every day show us the synergy of highly high combined value that has the potential to impact a multitude of complex logistics challenges.

Use case versus business case

These types of initiatives, where innovation and everything that it implies play a decisive role, we cannot manage under classic evaluation models based on a business case because, in most cases, we need to know the final net value of its implantation. Launching innovation processes 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 defines the business case.

The ethical aspects of the technology developed and implanted

Although, as always, the regulatory and legal aspects associated with technological developments are years behind their irruption, 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. 

At OGA, we are fortunate to be living together with our clients from the front line and in such a direct way, a time of logistics transformation as challenging and exciting as this, undoubtedly historic. We assume the responsibility of contributing, from the technical or functional role that each of us plays, so that their net contribution is as positive, sustainable, and profitable as possible.

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