IBM Z · z/OS · independent analysis

We show you where your MSU come from — and where they actually cost money.

We analyse z/OS environments from your own operational data: performance, cost, security and the factual basis for modernisation and migration decisions. No estimates, no agents on your system — measured data and a clear assessment.

150+analyses from one shared SMF data basis
Measurednot estimated — every statement traceable
AnalysisRMF, DB2, CICS, WebSphere
EN · DEanalysis, report and workshop in both languages

The costly misconception

Not every CPU second you save reduces the bill.

Under classic sub-capacity pricing, a single value determines the monthly invoice: the highest rolling 4-hour average. An application consuming 15 % of annual CPU work overnight, while the peak occurs at midday, saves — nothing when switched off.

Conversely, a small application with a sharp load profile can contribute disproportionately if it runs at exactly the wrong moment. To reduce cost you first have to know when load occurs, not only how much.

Capacity limit 00:0006:00 12:0018:00 24:00 MSU Rolling 4h average Consumption per interval billable peak
The jagged line is actual consumption. What you pay for is the smoothed curve — and of that, only the highest point of the month.

Scope

More than 150 analyses from one shared SMF data basis

Capacity and cost, workload and goal attainment, processor utilisation, jobs and transactions, database and application view — all from the same body of data, so the numbers fit together.

That is the real advantage: you do not have to reconcile values from different tools. What becomes visible at machine level can be resolved level by level down to the contributor — and the totals still agree.

Capacity & cost

Load peaks, smoothed curve, capacity limits, weights, group limits.

Workload & goals

Goal attainment per service class, delays, response times, prioritisation.

Processors

Utilisation of general purpose and specialty engines, dispatching, overhead.

Jobs & applications

Contributor rankings, runtime profiles, transactions, virtual applications.

01CECMachine, totalcapacity, physicalutilisation02LPARPartition, capacitylimits, cost impact03Job / STCThe actualcontributor, by name04TransactionResponse time andcost per unit of work05DatabaseAccesses, waits,share of resourcesANALYSIS CHAINEach level answers a different question — only together do they form a picture.
From the machine to the database call: every statement can be resolved level by level until the contributor has a name.

Market picture 2026

Leaving the platform is not the norm

Current user surveys paint a different picture from the headlines. That is precisely why an open-ended analysis is the more honest starting point.

3.2 %plan to decommission the mainframe within three yearsArcati Mainframe User Survey 2026
28 %of workloads earmarked for migration — down from 36 % the year beforeKyndryl State of Mainframe Modernization 2025
97 %see the mainframe as a long-term platform or for new workloadsBMC Mainframe Survey 2025
43 %name observability and performance monitoring as the biggest hybrid challengeArcati Mainframe User Survey 2026

All figures come from user surveys with self-selected participants and should be read accordingly. We deliberately avoid the widely quoted “failure rates” for mainframe migrations — none of them can be traced to a primary source.

“Capping systems and running them more restrictively means accepting delay.”

From a results presentation — the sentence that belongs in every cost optimisation

We always state the price alongside the saving. A recommendation without a named trade-off is not a recommendation, it is a sales pitch.

Let's talk about your numbers.

An initial conversation usually clarifies which data is needed and what scope fits your question.