Bridging AI Skills Gap Within The Logistics Sector

Bridging AI Skills Gap Within The Logistics Sector

August 22nd 2019

“The incorporation of Artificial Intelligence (AI) is a significant challenge facing Supply Chain Managers and Customer Success within the logistics space. As the logistics industry set to implement AI, what are the skill gap challenges and solutions to consider?”

The choice of product and availability is a vital part of excellent customer experience in retail. But proper delivery and logistics ensure any supply chain functions properly, and all purchases done by buyers arrive in good condition and time. Gradually, the last part of the delivery process is becoming a very crucial aspect. While it should not come as a surprise at all, progressively more goods and services are purchased online, either through box businesses retailers or door service retailers. These new business operations imply more logistics firms are transitioning from being a simple part of final delivery to the star that either break or make an exceptional customer experience.

With this new shift comes a massive prospect for logistics firms as the delivery of excellence guarantees more customers and reputation. Although not the easiest of the task, it entails a digital level of transformation within logistics. Such digital transformation includes more significant use of Artificial Intelligence (AI) solutions that ensures more effective, faster, and smarter process. The use of AI is a natural step to embrace for any logistics firm particular about retail and gets large data size.  A large amount of data aid AI and Machine Learning (ML) process in solving problems and discovering prospects. But it is also where the challenge starts.

To properly harness the power of AI, it requires having data scientist(s) who understand such data, can work with it and deliver useful results with it. So far, the competition of discovering and hiring these professionals is fierce. And with logistics companies not likely to own industrial and university ties to such talent pools, coupled with location challenges, hiring the right talent becomes a much harder task. The consequence is that in place of being able to seize the opportunity created by AI, logistics companies tend to look at the skills gap where such expert would fit. The question for pace-setting innovators within the industry remains “how to go about closing this gap.”

Why does logistics have AI skills gap?

AI is amongst the leading trend currently employed across the phases of all business process and industries. With the new role out from AI, nearly all CIO requires a capable hand to manage its operations. Regrettably, it also implies more firms would be looking to hire data scientist(s). The competitive talent markets are facing a reality that is only not having enough professionals trained to deliver desired AI, data analysis, and Machine Learning development. Consequently, the logical answer of hiring to fill the new roles becomes more difficult. In essence, the logistics sector does not always offer the most attractive proposition and is known to struggle in hiring young talent.

The skills gap presented by AI is one likely to force logistics firms to ask the all-important question “whether or not getting a data scientist is the best decision.” With technology development mainly recording a rapid rate, the improvement it offers the various aspect of the business should get considerations as well. Data scientists do not just require official training; they also require On-The-Job (OJT) experience. Data scientists also need to feature more commercial focus solution that delivers on the set goals for AI. With that in mind, the skills gap makes hiring a dedicated data scientist hard. Training non-specialist staff of the firm in AI becomes a sensible option for many, but:

First, you need to integrate the required AI skills into your business process.

Secondly, refute hiring from any expensive and small talent pool.

Effective Use of AI

Nowadays, the nature of logistics implies AI cannot exclusively be the domain for engineers and scientists. Its application and usage are set to expand into several job roles. A positive move, without doubt, the rise in AI-enabled solutions carries the question of how well educated in the whole labor force in understanding and utilizing AI. Specialized staffs from the board- to entry-level will required added training to understand how AI works and what roles it is set to play. Not necessarily to a data scientist level, but to a level that works for the system and develops data for further improvement in the process.

Leading AI technologies in logistics and retail allow various industries to apply tailored solutions across departments. Starting the process gradually, it grows as the technology learns from it. Given more data to work, AI gains better context and detail, which it finds useful in enabling a much smarter decision making and better efficiency process. Over time, the system will see less need for data scientists. Thus, it can find value in the hands of existing staffs. There is a massive prospect available with getting started with AI right now as it addresses several issues efficiently.

The business advantage of AI

AI’s potential is valuable to the logistics sector as it addresses several prominent challenges facing the industry. For instance, optimization under AI will become better with smarter route arrangement and optimal trucks filling. This process will sequentially imply more efficient trips, fewer vehicles, and decrease of tricky trips. It would also benefit logistics controllers in delivering a faster response to issues that arise during journeys. AI technology is capable of recognizing what happens and would automatically find the best approach and reply to these issues.

This possibility arises due to AI ability to seek solutions from various data sets in a way better than humans. Another example is UPS using AI to lessen its delivery miles to 100 million in the USA. The outcome results in an estimated savings of $50 million. In general, the industry can witness complete transformation if the right technology is employed, and people get the proper training power.

Closing the Skills Gap

AI implementation is everywhere; our businesses and personal lives are set to witness so much growth in the coming years. The skills gap we see in logistics today is not going away unless we embrace AI with speed and battle for recruitment of emerging and top talent. Large businesses are already spending millions in obtaining better data scientist capabilities within their business process. While such an approach may work for some, it may not be visible for others when considering cost and retaining talent.

For this reason, smart businesses are also tackling the AI skills gap using a mix of retraining and upskilling the AI technologies for essential staffs. Another approach employed is gaining access to top talent by partnering commercially-minded AI firms with the infrastructure, human resources, and solutions to executing AI effectively and swiftly. This approach seeks to harness AI’s predictive power for possibly millions of tasks required daily, permitting staff to place more emphasis on higher-level decisions.

CONCLUSION

We all can tell AI is going to revolutionary and enormously beneficial to the logistics industry. There is so much to gain and less to lose with the implementation of AI. But without the right AI technology and training to achieve these goals, the potential may not be realized. Adequate attention is required to thoroughly understand the skills gap within your business process and the possible AI solution to solving them. AI and big data is the next big thing for the logistics industry.