ASM engaged a partner because we have the knowledge of the tools and could rapidly distil answers.
Altered State Machine (ASM) is a collection of Artificial Intelligence / AI Metaverse companies based in Auckland, New Zealand.
INDUSTRY
Virtual World Tech
LOCATION
HQ Auckland, NZ
COMPANY SIZE
90+
ATLASSIAN USERS
90+
EG PRODUCTS
Capability & Tooling Roadmap
Solution Design
Product Assessment & Deployment
User Management & Access
Licensing Management
Managed Services & Support
APPS
Jira Service Management
Jira Work Management
Confluence
Opsgenie
Statuspage
Altering outcomes for the Futureverse with Altered State Machine
Altered State Machine (ASM) is a collection of Artificial Intelligence / AI Metaverse companies based in Auckland, New Zealand. ASM engaged Elegance Group to provide assistance and guidance on centralising multiple Atlassian organisations currently established across multiple companies within the ASM sphere.
The current independent set up, which includes over 300 unique users, had inefficiencies in account management, user access and non-standardised approaches to knowledge management. ASM wanted to rationalise licensing and form one “Futureverse” with an Atlassian ecosystem in the next 3 to 6 months.
Simply put, ASM’s goal was to consolidate their tooling, simplify their licensing and reduce overall costs by moving to a unified platform.
Our job was to analyse the current tooling, interview various stakeholders across the companies, consolidate the responses and provide a suggested pathway forward for ASM’s tooling and subscriptions.
It was critical to understand how people were working and what their preferences were for tools, as this has a direct impact on licensing options and pricing. This process presented the biggest challenge; dealing with a number of different companies that each had variations on how they used the tools and what they wanted from them.
The current independent set up, which includes over 300 unique users, had inefficiencies in account management, user access and non-standardised approaches to knowledge management. ASM wanted to rationalise licensing and form one “Futureverse” with an Atlassian ecosystem in the next 3 to 6 months.
Simply put, ASM’s goal was to consolidate their tooling, simplify their licensing and reduce overall costs by moving to a unified platform.
Our job was to analyse the current tooling, interview various stakeholders across the companies, consolidate the responses and provide a suggested pathway forward for ASM’s tooling and subscriptions.
It was critical to understand how people were working and what their preferences were for tools, as this has a direct impact on licensing options and pricing. This process presented the biggest challenge; dealing with a number of different companies that each had variations on how they used the tools and what they wanted from them.
Not all companies understood why we were engaged and naturally, some companies were more open to the idea of change than others. The interview process required a lot of emotional intelligence and sympathy to get engagement from key stakeholders from each company.
Once we had the information, we had to rapidly distil it and analyse it to produce a set of recommendations that were consumable to the average technical person. We also had to gain the trust of the security team at ASM by demonstrating that what we were recommending could be set up in such a way that provided them with all the features and capabilities they would need with a shared structure.
It was imperative that the recommendations delivered optimisation of the tooling at the very highest level; the use of domains, how ASM could implement security, and how ASM could collaborate more easily across companies and gain visibility and transparency to enable accurate and adaptable forecasting.
Ultimately, ASM engaged a partner because we have the knowledge of the tools and could rapidly distil answers, feedback and agendas from various stakeholders and turn that into something tangible they can make decisions from.
The result of our discovery was an in-depth report and set of recommendations that has driven internal direction regarding critical decision making for the coming financial year.
An example of something we discovered was, based on their current spend across the entire group, ASM could get between double and triple the seats at no extra cost if they were on a shared platform. This would allow ASM to scale without additional cost, and scale they will. To know that they don’t have to pay for additional licensing in the immediate future is a big win for ASM.
Once we had the information, we had to rapidly distil it and analyse it to produce a set of recommendations that were consumable to the average technical person. We also had to gain the trust of the security team at ASM by demonstrating that what we were recommending could be set up in such a way that provided them with all the features and capabilities they would need with a shared structure.
It was imperative that the recommendations delivered optimisation of the tooling at the very highest level; the use of domains, how ASM could implement security, and how ASM could collaborate more easily across companies and gain visibility and transparency to enable accurate and adaptable forecasting.
Ultimately, ASM engaged a partner because we have the knowledge of the tools and could rapidly distil answers, feedback and agendas from various stakeholders and turn that into something tangible they can make decisions from.
The result of our discovery was an in-depth report and set of recommendations that has driven internal direction regarding critical decision making for the coming financial year.
An example of something we discovered was, based on their current spend across the entire group, ASM could get between double and triple the seats at no extra cost if they were on a shared platform. This would allow ASM to scale without additional cost, and scale they will. To know that they don’t have to pay for additional licensing in the immediate future is a big win for ASM.