01 ViVE Optim
Insight, root cause and what-if analysis
One process. Every way it actually ran.
ViVE Optim is where analysts explore how a process actually ran — paths, timing, rework, bottlenecks, trends and root cause — with drilldown to the individual case.
02 What analysts come here to settle
Questions that usually get answered with opinion
Most operational arguments stall because nobody can produce the evidence quickly enough. Optim answers these from execution data, and shows the cases behind each answer.
- How many different ways does this process actually run?
- Where is the time going — working, or waiting?
- How much of the cycle time is rework rather than work?
- Which step is the constraint, and for which kinds of case?
- Why is this site or team slower than that one?
- Is it getting better or worse, month over month?
- Which change would give back the most days?
- Which individual cases are dragging the average?
How many paths, and how heavy each is
Every distinct route ranked by case count, share of volume and end-to-end time, with the tail kept intact rather than pooled.
Distributions, not just means
End-to-end, activity and transition times as means, medians and spreads, with waiting time separated from working time.
Where work is done twice
Loops and repeats identified by activity, with frequency, added time and cost attached to each.
Direction over time
Whether variants, rework and cycle time are converging or spreading, period on period, on the same definitions throughout.
Why, with drilldown
Cut any measure by attribute, resource, path or period until the explanation is specific enough to act on.
Standardization, automation, productivity
The three levers quantified against real execution, so the sequencing of an improvement program comes from evidence.
03 Process maps
The map is the measurement
RE-ViVE builds the process map from the underlying execution records, then puts the measures on the map: case counts, timing, waiting, rework and bottlenecks where they actually occur.
The map is generated from the Execution Data Model rather than drawn by hand. Counts, durations, waiting time, loops and skipped steps come from the same underlying execution data.
04 Root cause and drilldown
Keep cutting until the answer is specific
An average is where an investigation starts. Optim lets analysts move from the process figure down through variant, activity and attribute to the individual case, without leaving the module or losing the filter they arrived with.
- process
Customer onboarding
2.4M cases · 16.6 days average · 60% of elapsed time is rework
- variant
Documents returned twice before screening
318,000 cases · 24.9 days average · 13% of volume
- activity
KYC screening
5.4 of 6.2 days spent waiting · worst for corporate accounts routed offshore
- instance
Request ONB-4471902
41 days · nine events · two returns · one 14-day queue with no owner
| 08 Jan 09:14 | Request raised | Branch 214 | — |
| 08 Jan 16:02 | Documents checked | Onboarding team A | +0.3 d |
| 09 Jan 11:40 | Documents returned | Onboarding team A | rework 1 |
| 14 Jan 10:22 | Documents checked | Onboarding team A | +4.9 d |
| 15 Jan 08:55 | Documents returned | Onboarding team B | rework 2 |
| 22 Jan 14:31 | Documents checked | Onboarding team B | +7.2 d |
| 22 Jan 14:33 | Queued for screening | unassigned | wait 14.1 d |
| 05 Feb 17:09 | KYC screened | Screening desk | +0.2 d |
| 18 Feb 11:47 | Account opened | Ops center | +12.8 d |
The 14-day queue with no assigned owner is not visible in any average. It is visible here, and there are 4,100 cases like it.
05 Comparison
Same process, different results put side by side
Compare execution across periods, or across any dimension the source data carries: site, team, product, channel, customer segment, region. Because every comparison reads the same model, differences are real rather than artefacts of two teams measuring differently.
Comparison is where standardization cases are usually won. When one site already runs the process well, the target is not theoretical.
06 What-if analysis
Test a change against real execution first
Analysts can test proposed changes against the population that actually ran through the process. Remove a rework loop, split or merge an activity, add, delete or edit a step — then estimate the impact on cycle time, cost and volume before changing the operating process.
What-if analysis starts with the observed population, so the estimate reflects the paths, distributions and exceptions already present in the process.
Remove rework
Take a loop out and see how much of the cycle time it was carrying, and which cases stop being outliers.
Split or merge activities
Test whether combining two steps removes a handoff delay, or whether separating them relieves a queue.
Add, delete or edit a step
Introduce a check, drop an approval, or change where an activity sits, and read the effect on end-to-end time.
Read the impact
Cycle time, rework share, variant count and affected volume, for the whole population or any slice of it.
07 Where the improvement comes from
Three levers, quantified before they are chosen
Improvement programs usually pick a lever first and look for evidence second. Optim reverses that: the execution data shows which lever the process is actually asking for, and how much each is worth.
Standardization
When one site or team already runs the process well, the variance is the opportunity. Optim sizes the gap and names the paths responsible for it.
Automation
Automating a step that carries 4% of the elapsed time is a poor investment. Optim ranks candidates by the time and volume actually behind them.
Productivity
Separating waiting time from working time shows where capacity is genuinely short and where work is simply sitting in a queue nobody owns.
Where to point AI, and whether it worked
AI initiatives stall when nobody can show the execution baseline. Optim provides the before, the after, and the paths where the agent or model actually changed behavior.
Start with evidence, not discovery from scratch
Variant, rework and bottleneck measures give improvement teams a factual starting point before workshops and redesign begin.
What the customer waited for
Cycle time seen as the customer experienced it, including the returns and queues that never appear in a service-level report.
08 The rest of the platform
Optim is one of four ways to use the same process data
The same process data used in ViVE Optim also powers ViVE Comply, ViVE Insights and ViVE Genie, so teams do not rebuild the process for each use.
ViVE Comply
SLAs, mandatory and sequenced activities, segregation of duties, and X-R and X-S controls — monitored against real execution.
ViVE Insights
Drag-and-drop reports and dashboards over the Execution Data Model, built the way your team wants to monitor the process.
ViVE Genie
Ask questions in natural language using the same RE-ViVE process data, with your SOPs and designs available as additional context.