Tailored Fit Pricing – How to control costs in a world without the R4HA or DC
What is Tailored Fit Pricing？
In May 2019, IBM announced a new pricing model called Tailored Fit Pricing introducing containers and a new billing methodology. In particular, with the Enterprise consumption solution, costs are no longer linked to the consumption peak but to the cumulative quantity of MSU consumed during a year. Basically, the customer commits to an annual cost related to an annual amount of cumulated MSUs and pays 1/12th of this amount each month. This pricing model changes the way MSUs are accounted for.
IBM introduced Tailored Fit Pricing to make the Z platform more attractive for implementing new applications and make it possible to test new types of, potentially volatile, workloads without drastically affecting consumption. Previous pricing models, which relied solely on activity peaks, were susceptible to huge variances in costs due to unpredictable workloads. It has become clear that this issue unfairly bars many z/OS environments from realizing growth potential.
“While once batch activity prevailed, today’s workloads tend to be primarily transaction-oriented,” according to an IBM press release. “Real-time analytics on data to gain insights, smartphone-driven transactions, and other market factors are driving workload volatility. This volatility impacts workload costs and has prompted the need for a pricing solution that aligns costs with actual resource usage.”
Put simply: mainframe activity has evolved and so must pricing models. Tailored Fit Pricing is designed to overcome unpredictable expenses associated with the pricing models that put far too much emphasis on activity peaks.
Why does it complicate cost control strategies？
When a customer decides to switch to a Tailored Fit Pricing model, the idea is to simplify cost readiness and visibility. Similar to a well-known method borrowed from electricity or water suppliers, every single MSU counts. That could not be easier to understand. But at the same time, it is no longer an option to rely solely on soft capping mechanisms to control costs as the only way to stop MSU consumption would be to shut down programs, which of course is not an option.
In this regard, customers need to be able to monitor their consumption in real-time in order to know where they stand against their contractual agreements and to be responsive in the event of abnormal consumption.
In addition, containers are not all invoiced on the cumulative consumption of MSU. The most complex aspect of this new model is that dev & test environments will continue to be invoiced on consumption peaks and the Rolling Four Hours Average. Sure, IBM is offering the ability to choose a high baseline for their dev/test container but by doing so, customers will face a cost increase for their IPLA products (e.g., One-time-charge licenses).
In short, under Tailored Fit Pricing, customers will need to manage both worlds at the same time to remain in control of their budget.
How to ease the process？
Firstly, capacity reporting and automation solutions are still relevant for customers with Tailored Fit Pricing solutions, given that they could adjust capacity allocation strategies based on container types:
- Dev & Test environments are still working under the R4HA model. To stay under the limit of your contractual baseline, you need to dynamically adjust defined capacities on the dedicated LPARs.
- Enterprise Consumption environments need closer monitoring as every MSU counts. Knowing exactly what is running on your mainframe in real time is thus the key to staying within the limit of your commitments.
- Real-time alerting systems for each environment ensure quick actions can be taken when abnormalities occur.
Furthermore, if you happen to be a mainframe outsourcer, the tailored fit pricing model is just out of the picture. IBM reserves this model for their direct customers who are also ready to commit to activity growth. In this situation, capacity automation solutions are key in ensuring costs stay under control, especially in an environment supporting multiple customers at the same time, each one requiring specific capping parameters based on their actual resource consumption.
In this regard, Zetaly offers Zetaly Automated Capacity.
Secondly, observability solutions offer the ability to get a broader picture of your mainframe environment and its links with your entire infrastructure in order to make the best management decisions.
The best way to optimize your IT budget in the age of Tailored Fit Pricing is to learn where your money is going. It’s as simple as that. Under Tailored Fit Pricing, budget and financial adjustments will be made on a per-MSU basis, so it’s more important than ever to know what is occurring on your system, and, more importantly, what value that activity provides.
What does this mean for mainframe managers? With a greater focus being put on MSU consumption, IT teams will need a way to collect, monitor, and analyze mainframe logs with greater efficiency.
With Zetaly Service Intelligence, gain in-depth, real-time consumption info that directly reflects your working environment. Through customizable, adaptable dashboards, users can visualize MSU relationships that would normally go unnoticed. With this unprecedented insight, you can make strategic adjustments to help maximize mainframe efficiency and affordability.
Finally, Zetaly Cost Control illustrates expenses down to the departmental level, so you can align business needs with IT costs. No more abstract spreadsheets — Zetaly gathers information about MSU consumption and makes it clear which business needs are being served by mainframe activity. This information is displayed in easy-to-understand reports so everyone can understand and, more importantly, be held accountable for the mainframe budget.