A customer story of Enterprise onboarding

Company

Global Enterprise

AI method

Text classification, tabular regression, text similarity

Industry

Manufacturing

Recently, Peltarion has been working with a large manufacturing enterprise to transform their current AI innovation hub from a purely centralized, concept-based, non-operational effort into a democratized, value-focused, operational AI initiative, through the AI enablement of both domain and business experts within the organization. 

In this article, we will take a deeper look into the onboarding journey of this Enterprise, from AI ideas to operational AI.

02/ The Background

The Enterprise reached out to Peltarion looking to explore the possibility of utilizing our AI platform to scale their AI innovation efforts. The organization had been experimenting with AI for a number of years, with a few full-time data scientists on staff and a centralized innovation hub, where the focus was on the ideas, rather than on the value-add of those ideas, with no operational AI projects. 

With the goal of moving from this to applicable value creation, the Peltarion team started the onboarding process with the two teams involved from the Enterprise.  

03/ Enterprise Onboarding Quicksheet

The main goal of onboarding is to AI-enable the organization’s domain experts - who are not AI-experts themselves. AI-enablement means giving the people with the ideas some fundamental knowledge and a tool, that coupled with data, can be used by these domain experts to solve their own AI problems. 

At the end of the onboarding, the individuals and teams involved should have accrued a high-level knowledge on how to solve typical AI problems on their own with the help of our platform. Enabling AI in the organization is key to the onboarding process, regardless of the team’s initial skill level.

04/ The onboarding work: kicking off the journey

The individuals involved were divided into two teams of similar size and make-up of business-oriented roles. One of the teams had a use-case idea that Peltarion set out to help them realize, and the other team had no specific idea, but were interested in learning more about AI. 

As a starting point, we began a kickoff set of sessions where Peltarion shared theoretical and practical AI knowledge and in-the-field experience through webinars and interactive platform sessions on weekly 90-minute meetings, over a period of 8 weeks. 

Topics included an introduction to AI and general AI knowledge, problem solving with AI and what that process can look like, platform onboarding - know-how practical sessions where we collaboratively built AI models on the platform. 

In this stage of the onboarding process, we collectively worked with the teams to find out which components enabled them to become successful in an AI project.

05/ Proof of value: driving use cases through the funnel

Once clear-value use cases were identified, the teams worked with our AI Experts to determine the availability and the usability of the data needed for each use case, framing each idea into an AI problem. The data was uploaded onto the Peltarion platform, targets were selected and the AI models were then created, trained and evaluated.

06/ On to AI operationality

At this stage, the Enterprise was now equipped with AI-enabled domain experts, allowing them to use the latest deep learning techniques to carry their AI projects forward, without the need to invest in expensive AI experts in the business lines and without relying on the previously centralized team to not only find all the ideas but also to carry onwards all those ideas - which is not feasible. 

Enabling the domain experts to use AI also results in freeing up valuable time of the few data professionals this particular enterprise had on payroll so that they can focus solely on the very high complexity cases. The value being created from AI with this approach can easily be 10 times higher in comparison to Enterprises working with only a centralized team.

The two teams are currently moving on to the piloting stage where our AI Experts support them in validating and interpreting their models’ results and the long-tail business impact of the projects.

07/ Next steps

After the theoretical and practical learnings and going through the use case funnel, teams should feel confident in developing the ability to solve AI problems self sufficiently. Peltarion will continue to work with this Enterprise, offering continued support for the individuals that have completed the onboarding sessions, thus allowing them to continue building their AI-solutions, as well as providing new licenses and new onboarding for new teams, expanding the Enterprise’s AI footprint.

Confidently possessing AI knowledge regardless of technical background and having a self-service AI tool to develop and manage value-adding AI solutions enables the domain experts of an Enterprise to create business value quickly, affordably and in-house. 

Inspired? Send us a message and we’ll gladly enable your Enterprise’s AI efforts at whichever stage of the journey you may be.