AI-enabled efficiencies offered by startup Seebo could ease labor challenges, help attract top talent

By Elizabeth Crawford contact

- Last updated on GMT

Source: Getty/ ablokhin
Source: Getty/ ablokhin

Related tags: AI, labor shortage

Israeli startup Seebo may be best-known for helping food and beverage companies, like Barilla, Nestle, Mondelez and PepsiCo, predict and prevent food waste, but its Process-Based Artificial Intelligence technology also can help companies navigate one of today’s biggest challenges: labor shortages.

According to the Labor Department, the number of job openings in the US reached more than 10 million in June – the highest on record – and despite offering signing bonuses, better benefits and wages that are 4.6% higher on average for food manufacturing positions and 6% higher for production and non-supervisory roles than a year ag​o, many food and beverage companies are struggling to fill vacancies.

As a result, some can’t meet rising consumer demand for their products because they don’t have the employees necessary to run lines, oversee production, transport supplies and finished goods, and perform other essential jobs.

Seebo offers relief by using its AI technology to maximize the efficiency of existing employees, helping to attract top talent and offering remote assistance to bridge lingering gaps, COO and co-founder Liran Akavia told FoodNavigator-USA.

He explained Seebo can help businesses make the most of the employees they have the same way that it helps them improve the efficiency of their production lines to reduce waste and cut costs.

“There is a tight relationship between an excellent team and an excellent line. In other words, if you have a team that is not excellent it is very difficult or sometimes impossible to get an excellent performance on your line,”​ Akavia said. “But one of the things that we do with the teams that we work with is to disconnect this relationship to enable an ‘okay’ team to run an excellent line.”

He explained Seebo does this by using artificial intelligence to analyze the outcome of the production line, the product throughput, quality, waste and other data on the production line to identify inefficiencies, why they are happening, where they are happening, how to prevent them and when the production team should act.

This process allows “okay teams” to get the same “very smart results” as an excellent team because it elevates the information on which they can base decisions.

By gathering essential data in one place and leveraging AI to analyze it, Seebo can also offer remote assistance to companies with multiple locations. This means one expert can easily review the data and production of all the facilities, rather than needing an expert at every facility.

“This is a game-changer” ​for companies because it reduces their talent requirements without sacrificing output, he said.

On the flip side, Seebo can also train and assist employees to punch above their weight – allowing companies to train and elevate “experts” at different if they’d rather have someone at each location, Akavia added.

Seebo further supports team members by making institutional knowledge more accessible in an electronic, easy-to-search or automated format.

Akavia explained, if an employee has a question about a process or is unfamiliar with all the steps in a procedure, Seebo can save them time looking up the answer in a manual or compliance manual typically stored “somewhere in the cupboard behind them” by instead prompting them with automated alerts. This also reduces pressure on supervisors who may be stretched thin in today’s labor environment.

Finally, Akavia said, Seebo can help attract top talent who are looking for opportunities to expand their skillsets and learn cutting edge technology.

“We’ve heard different team members say that [Seebo’s technology] is cool or sexy and they like having access to the latest tools. So, if someone is interviewing for a job at a big manufacturer and they hear that [the company] runs artificial intelligence, they might be more likely to choose that job so that they learn and use the latest tools,”​ and build their career, he said.

Ultimately, he said, Seeba strives to “provide the right solution in the right place so that [turnaround is] shorter”​ and the external labor inputs are lighter.

‘We would like to make a real impact in the relationship’

Seebo is not a panacea though – rather, it works best in highly technical, complex and automated lines, and is less effective in manual operations.

This is why before Seebo teams with a company it always qualifies a potential partnership and conducts a gap analysis.

“We would like to make a real impact in the relationship, which is why we always start with qualifying a business case,”​ Akavia said. “So, we sit down with the manufacturer, ask questions to understand where it hurts, understand the financial value and do some calculations with different methods to understand our impact.”

If that impact justifies the investment, Seebo conducts a data gap analysis.

“Not all food manufactures have enough data to feed artificial intelligence,”​ Akavia said. “But when you do, with an expert and a specific business goal that will make the process more focused … then we can provide very efficient, very accurate answers”​ with less of a time and financial investment.

Once the data is in place, Seebo teaches the team how best to use the insights to generate solutions – a process that is not necssarily intuitive, which is why Seebo uses a visually-heavy interface that makes it easier for people to understand what they are seeing and what changes they need to implement, if any.  

While companies must have sufficient data to run Seebo’s technology, Akavia is quick to note that companies do not need to be fully automated to benefit from the AI.

“We see everything from top-notch plans at companies with excellent supply chains that are just looking to optimize the extra mile to stay very competitive to very early plans that are somewhat behind the technology and the owner of that line wants to take them from zero to 100,”​ he said.

Expect to breakeven within a year of investment

Given many companies are grappling with rising inflation and may be looking for ways to cut costs rather than invest, Akavia said Seebo prides itself on paying for itself within the first year if not sooner.

“One of the reasons we are so careful to determine if there is a viable business case before partnering with a company is because it is important to us that our clients breakeven within less than a year,”​ he said.

“For many manufacturers, that changes the conversation because within the same financial year or same budget you are going to pay, invest and then get at least that amount or more back,”​ he said.

While he couldn’t share specific numbers, he noted that when Barilla partnered with Seebo, it reduced its waste by 37% in less than a year, which is “meaningful because it has an excellent impact on the business from one hand, and from the other hand on the satisfaction of consumers seeking more sustainable products.”

Related topics: Suppliers, COVID-19, Markets, Manufacturers, R&D

Related news

Show more

Follow us

Products

View more

Webinars