Portfolio Analytics Dashboard: The Cross-Process View That Makes Transformation Programmes Defensible

Portfolio Analytics is built for two specific users: the small-and-mid-sized business that is mapping 10 or more processes internally, and the consultant who is running transformation engagements for five or more clients at the same time. Both need the aggregate view before deciding where to attack the AI transformation first. Everything below explains how the eleven metrics support that decision.

For the first one to four processes in your workspace, the individual process dashboards are enough: cost per execution, monthly burn, top three drivers, per-process heatmap. The question the data answers is always 'is this process worth optimising', and the answer is visible from the single-process view. Past four or five processes, a different question becomes dominant and the single-process view cannot answer it. The new question is 'across the organisation's whole process portfolio, where does the cost actually live and where should we focus'.

This is the question the Portfolio Analytics dashboard is designed to answer. It aggregates across every process in your workspace: the BPMN nodes, their KPI payloads, the detected automation potential, the role assignments, and produces eleven specific data points that summarise the whole portfolio. For Enterprise-tier customers running transformation programmes across multiple departments, this is the view that turns a collection of individual analyses into a defensible strategic artefact.

The dashboard computes eleven specific metrics from your portfolio, each answering a different strategic question. The specific eleven are not a design choice; they are the minimum set that makes the 'where should we focus' question answerable.

• Total processes: the baseline count, usually the first thing an executive looks at.
• Total processes optimised: how many have had a structural optimisation applied, surfacing the coverage gap.
• Total processes with AI plans: how many have an ESSII transformation plan generated, surfacing which processes are ready for the next phase.
• Total annual cost: summed across every process, the single biggest number on the dashboard and usually the one that drives the 'we need to prioritise' conversation.
• Total annual savings: summed across every process. The per-process projection uses the formula `15% + (automationPotential ÷ 10) × 5%`, capped at 45%. So a portfolio whose tasks are mostly low-automation-potential lands near 15% of annual cost; a portfolio that is mostly automatable approaches the 45% cap. The aggregate is whatever the per-process projections add up to.
• Average annual cost per process: useful for sizing the investment required on each new process that gets added to the portfolio.
• Role cost breakdown: percentage of total portfolio cost attributable to each role across every process. This is where systemic insights appear: if Finance accounts for 28 percent of portfolio cost across 12 processes, the bottleneck is organisation-wide rather than process-specific.
• Top 5 most expensive processes: ranked by annual cost, each with a link into its detail view.
• Top 5 biggest savings opportunities: ranked by projected annual saving, which is often a different list from the most-expensive-processes one because some expensive processes have low automation potential.
• Automation potential percentage: aggregate automation score across the whole portfolio, computed by the pattern-matching classifier running on every task.
• Overall portfolio efficiency score: a single 0 to 100 index that blends cost efficiency, automation coverage and optimisation coverage into one number for executive reporting.

The role cost breakdown is the dashboard view that consistently surprises users the most, because it surfaces insights that are invisible at the single-process level. On any given process, one role might look bottlenecked but the cost share is a single-digit percentage of that process. Aggregated across 12 processes, the same role often turns out to be the single largest slice of total portfolio cost, and that is a strategic signal rather than a process-level one.

The typical pattern for a mid-market company: Finance and Operations together account for 40 to 55 percent of total portfolio cost, with the remaining 45 to 60 percent distributed across Sales, Support, Engineering, HR and Legal. The Finance-and-Operations concentration is usually a surprise because no single process shows it; it only emerges when the view is organisation-wide. The strategic implication: an AI transformation programme that focuses solely on one process at a time will miss the role-level concentration and leave the biggest savings on the table.

The dashboard is designed to answer three specific strategic questions in under a minute each, without needing to drill into individual processes.

1. Where does our process cost live?

Look at total annual cost, then the role-cost breakdown, then the top-5 most-expensive processes. Three numbers, three views, roughly 30 seconds. The combination tells you the aggregate number, the organisational distribution, and the specific processes driving the distribution. This is the read that answers 'is our cost concentrated or distributed': most organisations discover it is more concentrated than they thought.

2. Where should we focus next?

Look at the top-5 biggest savings opportunities, not the top-5 most-expensive processes. The two lists overlap but are not identical: some of the most expensive processes are fundamentally human-judgement work where AI cannot help, while some mid-expense processes are entirely pattern-matching work where AI drives huge savings. The savings-opportunity list is what should drive your roadmap decision; the most-expensive list is context.

3. Are we making progress?

Look at processes-optimised and processes-with-AI-plans as a ratio of total processes. These are leading indicators of realised savings: a portfolio with 70 percent of processes optimised and 40 percent with AI plans is further into the programme than a portfolio with 20 percent optimised and 5 percent with AI plans. The portfolio efficiency score rolls these together into a single number that a board can track quarter-over-quarter without needing to understand the sub-metrics.

The portfolio view is a prioritisation tool, not a plan. For an SMB running 10+ processes or a consultant juggling multiple clients, its job is to answer the single question "which process do we transform first" and defend the answer with data. Once that is settled, the AI transformation plan takes over on the chosen process. Portfolio Analytics points at the target; the per-process ESSII plan tells you how to hit it.