“Saved ~$1.7 Million in Just 30-days”
Ironically, his team had one major advantage: with the merger and associated activity still fresh, they “had a decent understanding of what it will take to separate from GE”.
In July 2017, the then Baker Hughes International Inc. (BHI), merged with General Electric Oil and Gas (GEOG) to become Baker Hughes, a GE Company (BHGE). This merger provided several special benefits, including “access to GE’s impressive buying power, IT infrastructure, new technologies, business processes and overall global strength.”
Unfortunately, the two organizations functioned differently and integrating the two legacy businesses required massive changes. “…things quickly became very difficult.”
GE’s underlying infrastructure was to become the new organization’s (BHGE) standard. This included pcs, servers, networks, identity management and HR systems.
“The challenges we were facing were significant: almost every time there are two typical options… Legacy BHI had deployed a different strategy in GE’s.”
Such strategy differences included how users accessed and engaged digital systems, empowerment, software cost budgeting, infrastructure costs, on premises/cloud servers, etc.
Though neither option or philosophy was wrong, the problems existed and had to be resolved. However, other events rapidly took over.
GE always planned to reduce their ownership. However, in late 2019, the separation was triggered when ownership dropped below 50%: Baker Hughes, a GE Company (BHGE) became Baker Hughes (BH). Separation was a massive undertaking that would take several years.
For BH, the separation provided the ideal opportunity to investigate and implement new direction and strategies, especially with engineering software monitoring and management. The team outlined their goals.
Effective Software Monitoring
• Quantifying demand – the tools, their location, accessibility, and for how long, etc.
• Aggregating enterprise-wide data usage – across all networks/systems to improve visibility and reporting, pool size analytics, etc.
• Reducing administrative costs – aggregating data via pool size optimization (plus quantity offered) including site/region v global licensing.
• Reducing renewal, pool expansion and sharing costs – leveraging buying power, group annual spends by software publisher, project cost tracking, etc.
• Divestiture and acquisitions – greater visibility and understanding of existing pools and capacity plus ensuring compliance.
Efficient Software Management
• Consistent Deployment – active software management and compliance, addressing denials of service, automated notification of services going down, dedicated admin, and support teams, etc.
• Access control – capture usage per user, block unauthorized users, and check for non-compliant use, etc.
• Automating software release – for idle and hung sessions as well as license service restarts.
• Preferred Tools – proactively encourage and communicate use of preferred over non-preferred tools.
It was while BH were investigating licensing options that someone at GEOG mentioned OpenLM.
The $120,000 Recommendation
GEOG deployed OpenLM on a 500-user SolidWorks account to manage and enable cost sharing/billback within a large business group. OpenLM saved them $120,000 on SolidWorks renewal costs and, following their recommendation, the BH team decided to evaluate OpenLM.
“Ultimately OpenLM proved out to be the better choice based on futurist price and history of customer support.”
BH trialed OpenLM with Ansys.
The Ansys Use Case, OpenLM, and plugging that $2.7 million Gap
Following the merger, BHGE benefited from GE’s special seemingly limitless capacity and surge and demand relationship with Ansys: “users enjoyed having what they wanted when they wanted it.” However, following separation, this capacity and access ended. Suffering “…significant denials of service that broke many of the automations and routines” led to additional problems including “people began to hoard licenses, not releasing them back to the pool…”
Such practices further stressing an already fragile ecosystem.
“Fortunately, we had recently deployed OpenLM and we’re monitoring Ansys pool.”
Steps to resolution
BH outlined 5 essential steps to resolution:
1. Focus – identify and quantify exactly what is being used.
2. Monitor – observe and understand the situation.
3. Control – implement required controls.
4. Behavior modification – quantify the problem.
5. Purchase the gap – between current capacity and likely capacity.
OpenLM’s native reports allowed BH to, first, identify the features in use and to guide them on additional evaluations. Subsequently, they could contact users and educate them in better understanding the licensing situation, as well as offering viable alternatives including using other features and rescheduling jobs. Furthermore, these reports also provided a clean and simple means of determining seat usage (ensuring a specific level of availability) and offered clarity in visualizing overall problems. One test, which showed OpenLM’s native heat maps capturing peak usage periods, proved remarkably effective.
The effectiveness of OpenLM
From May 6th to June 6th, BH tested their ‘Ansys Mechanical’ product…
“…an expensive package, we own 79 seats.”
• May 6th – all 79 owned seats were used (79/79).
• May 7th – Ansys provided an extra ‘temporary pool’ of 25 seats. All were used (104/104).
• May 12th – To better understand our maximum capacity, Ansys added another 475 temporary pool seats (138 of 500 were used).
• May 20th – at peak, 155 seats are used (155/500). On average, approximately 130 were used:
• May 22nd – users were informed of preference changes. Peak usage decreased from 155 to 140.
• June 6th – users were asked to release idle sessions; usage dropped to 90 to 100 (of 500)
As Jason said, “our plan is to have all licensed services monitored with OpenLM, and as many as we can be hosted in our licensed server farm.”
(May 6th – June 6th)
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