H&M, Leading Retail’s Way in AI
Realising there was a gap in the market and that AI could present a competitive advantage, H&M saw an opportunity to take a lead position.
"We were, of course, very good in some aspects, like CRM, like buying, controlling and the traditional aspects of retailing. In the past, when we were buying too much, we could just open a new store, but we wanted to be more precise. We wanted to minimise waste and really harness the value of AI," said Errol Koolmeister, product area lead engineer for AI Foundation at H&M.
In 2016 H&M started with AI at the group level, leading to the launch of the first use cases, selected based on value and feasibility. Koolmeister explains, "We wanted to pick the low hanging fruit, the biggest fruits. First, we didn't have the capacity to run these type of use cases internally. When you're just starting out, you don't have the amount of people that's required to drive an AI use case at that scale, so we went with an external consultancy firm. We got approximately 100 resources in and started focusing on value. That was the key aspect all along. Let's not build the most advanced models; let's build the ones that generate some sort of uplift and bring the value back so we can keep funding these type of initiatives".
Within the first year, the initiatives were self-funding. By 2018, AI had its own function and resources, including budget and staff, becoming the first new corporate function in H&M in over ten years.
When Covid-19 hit, instead of slowing down, the company decided to pick up speed.
"In the middle of our great plan, COVID kicked in," said Koolmeister at the AI Business Week event. "We decided we really needed to push forward with everything". H&M's vision became to "make H&M Group the industry leader in applied AI with scalable and integrated solutions covering the entire value chain".
Objectives were to reduce time-to-market for use cases, provide AI tools to all product teams, improve AI literacy and contribute to an increased skillset in tech, as well increase outputs such as demand forecasts for all. However, the much talked about talent gap suddenly became very real.
Koolmeister on The Very Real Talent Gap
"Even [if] we put in a lot of money, we still wouldn't have the resources because there truly is the war for talent. In the use cases that we were building, we realised there was some basic duplication. They were moving fast, and they were agile, but given that we did seven or eight use cases, all running independently and autonomously to provide value, there was a lot of things being invented over and over again. We also saw in the beginning that there were long development times. Even though time-to-value was relatively short compared to some other cases I've heard, we thought that 12 months was too long. We wanted to bring that down into weeks.
"We also realised there was a lack of engineering knowledge. Of course, you could hire a lot of engineers into AI, but if the organisation wasn't really ready to take it over and run with it, that was hard. And we also thought that our process of starting new cases was relatively inefficient. We wanted to become a machine to start doing things again and again and again… What we realised as well was [that] there was a relatively low data and AI literacy across the organisation".
"Fountainhead" is H&M's platform designed to focus on "democratising" AI throughout the company and intended for use with hundreds, possibly thousands, of use cases throughout the organisation.
"We wanted to make AI available across the entire H&M group," said Koolmeister.
Facilitating scalability was the key for H&M to more deeply incorporate AI into the enterprise. "For us, it was mainly about creating foundational teams that facilitate the scale of AI capabilities," Koolmeister said. "Rather than going by use case to use case, we focus on training and development."
Building foundational capabilities included exploration and research, knowledge capture and management, training and development, quality assurance, AI risks and ethics, data science tools and supply chain and vendor management.
Koolmeister says the framework delivered value by reducing time-to-market for use case development by 50 per cent. That 12 months he complained about? Well, it's now six.
JAGGAER: Advancing Procurement Technology in Healthcare
JAGGAER has revealed the latest technological advancements in its cutting-edge, ground-breaking system at this years Arab Health, hosted by Informa Markets, as the industry-leading all-in-one procurement platform provider continues to provide support for the global healthcare industry as it struggles to recover from a year and a half tainted by the novel Coronavirus, and the ongoing pressure that it is putting on hospitals and pharmaceuticals.
With new technology and innovation taking centre stage this year’s edition of Arab Health, JAGGAER announced the launch of its new ‘Digital Mind’ strategy. The strategy features a core set of advanced strategies, including embedded intelligence, predictive data analytics, and real-time user guidance that can all be used to support healthcare procurement teams with the necessary and oftentimes difficult strategic decision-making involved in the acquisition process. It’s set to better efficiency across the sector, reduce risk, and better customer service capabilities.
The Exponential Growth of IoMT
This development comes at a time when the Internet of Things (IoT) has started to infiltrate all industries in an elaborate way. In a report published by Deloitte, it has been suggested that the global market for the Internet of Medical Things (IoMT) is projected to exceed US$158bn by 2022, with the IoMT market specifically in the MENA region, expected to hit US$9bn.
Hany Mosbeh, Vice President of Sales Middle East & Africa, JAGGAER, said: ‘The healthcare sector is increasingly adopting disruptive technologies into the IoMT ecosystem including artificial intelligence (AI), augmented and virtual reality (AR/VR), and robotic process automation (RPA). From a procurement perspective, these technologies are also being utilised in our systems, having far-reaching benefits for the healthcare industry.’
JAGGAER’s Digital Mind
The new Digital Mind strategy incorporates JAGGAER Adopt, Assist and Advise. The latter of which enables users to be more proactive in recognising potential areas of improvement and mitigating challenging situations such as supplier risk. By leveraging a combination of advanced predictive analytics, machine learning, and customer-specific business rules, JAGGAER Advise empowers procurement professionals to identify steps that could improve performance or results and take corrective action on behalf of users.
The software also provides its users with data-driven actionable insights and recommends the next steps to mitigate the risk of supply disruptions, supplier qualification, performance issues, and underperforming sourcing events.
Speaking at one of the sessions during the event, Microsoft Research’s Chief Medical Scientist, Dr Junaid Bajwa, outlined the role of data in the healthcare sector, he said: ‘Today’s story is one of automation of processes, aggregation of data, moving to intelligent analysis and AI, and then repeating that cycle. If we get this right, it has the potential to reduce costs and support clinicians by unmasking occult disease types, generalising new associations and perhaps even generating new novel hypotheses and new mechanisms.’
Right now, JAGGAER supports over 120 healthcare organisations globally. They do so by modernising and transforming their procurement capabilities through digitalisation─an action that is propelling the industry forward at pace. To name just a small number of companies that JAGGAER services: Dubai Health Authority, Uniting Care, NHS England, HCA Healthcare, and Bright Horizons.
‘During Arab Health, we heard from a range of experts who highlighted the challenges directly linked to COVID-19, from developing enough vaccines to combat the infection to the flow of raw materials to make the vaccines. In an era of technological advancements in the healthcare industry that are saving lives, it is also important to utilise this technology from a business perspective so that we can identify future risk and improve performance’, Mosbeh added.