For Enterprise
Same data. Different conclusions. That is your problem.
Every department has dashboards. Every team has its own definitions. Every quarter, someone asks "why did revenue move?" and the answer depends on who you ask. KPI Tree gives your organisation a single, governed model of how metrics connect, who owns them, and whether the actions being taken are actually working.
You invested in the data stack. The decisions did not improve.
Enterprise data infrastructure is sophisticated. The problem was never access. The problem is that no tool connects what happened to why it happened, who should act, and whether that action worked.
Every department has its own truth
Marketing measures leads. Sales measures pipeline. Finance measures revenue. Nobody can trace the causal chain between them. When a number moves, the post-mortem is a room full of people pointing at different dashboards, each telling a different story about the same quarter.
Hundreds of metrics, no named owners
Your organisation tracks hundreds of metrics across dozens of teams. When something goes wrong, the first question is "whose metric is this?" and the answer takes longer than the fix. Metrics without owners are metrics nobody manages. They get reported on. They do not get improved.
More dashboards, less understanding
Your organisation has thousands of dashboards built to answer thousands of questions. But not one of them shows how the pieces fit together. People have access to more data than ever. Executives still make decisions on instinct, because the data tells them what happened without telling them why.
One definition. One owner. Every metric.
Define your metric taxonomy once and make it the shared language of the organisation. Every metric has a single canonical definition, a named owner, and a clear position in the causal structure. When the CFO says "revenue" and the VP of Sales says "revenue," they mean exactly the same thing. The arguments about definitions end. The conversations about what to do begin.
- Canonical metric definitions shared across every team and department
- Full audit trail on every change to definitions, ownership, and structure
- Role-based access controls that map to your organisational hierarchy
- Version history showing how your metric model evolves over time
Named ownership that changes how people act
Every metric in every department has a person whose name is next to it. Not a team. Not a department. A person. When a metric moves, that person knows about it within minutes. When they take action, it is tracked against the metric it was meant to improve. Two weeks later, they can verify whether it worked. This is the closed loop that every analytics platform claims and none of them deliver.
- Assign owners, contributors, and stakeholders to every metric in the organisation
- Automated notifications via Slack, Teams, email, WhatsApp, or SMS when metrics shift
- Actions tracked against the specific metric they target
- Impact verification that closes the loop between action and outcome
Sits on top of the stack you already built
KPI Tree does not replace your data infrastructure. It consumes metrics from your semantic layer, warehouse, or BI tools and adds the layer those tools were never designed to provide: causal structure, named ownership, and a closed loop from metric movement to verified human action.
- Native integration with major semantic layers
- Direct connections to all major cloud data warehouses
- Pull metrics from your existing BI tools
- API-first architecture for custom integrations and embedding
Security and compliance without compromise
Your governance requirements are non-negotiable. KPI Tree is built for organisations where security reviews are thorough and compliance is mandatory.
- SOC 2 Type II certified
- Single-tenant deployment available
- SSO via SAML 2.0 and OIDC
- Data residency options for regulatory compliance
“Your BI tools show what happened. Your strategy tools track whether goals are aligned. Nothing shows why metrics moved, who should act, or whether the actions worked.”
The missing layer in your data stack
Analytics platforms give you faster answers. KPI Tree gives your organisation the structural understanding of how metrics connect, who is responsible, and whether the actions being taken are making a measurable difference.
Causal structure, not dashboards
A metric tree is a causal model of your business. Every relationship has a direction and a measured strength. When people see cause and effect instead of charts side by side, they reason about problems differently. That shift in thinking is the point.
One model across every department
Marketing, sales, product, and finance see their metrics in the same structure for the first time. The conversations shift from "what happened to the numbers" to "what are we going to do about it." That is the difference between reporting and performance management.
Enterprise-grade from day one
SOC 2 Type II, single-tenant deployment, RBAC, full audit trails, and dedicated SLAs. Your security team will not need to make exceptions.
Common questions
- Your semantic layer ensures metrics are defined consistently and delivered reliably. That is the foundation. KPI Tree adds what no semantic layer provides: the causal relationships between metrics, named ownership of every metric, actions tracked against outcomes, and verified impact. Your semantic layer solves the definition problem. KPI Tree solves the "so what do we do about it" problem.
- Every metric has a designated owner, along with optional contributors and stakeholders. Ownership syncs with your identity provider via SSO and maps to your organisational hierarchy. When a metric moves beyond expected ranges, the owner is notified automatically through their preferred channel. When they take action, it is tracked and verified. At scale, this creates a culture where metrics are actively managed, not just reported on.
- Your BI tools define metrics and display them. KPI Tree models how metrics cause each other. Your BI tool can tell you revenue dropped 8% last week. KPI Tree shows you that the drop traces to a conversion rate decline in a specific segment, caused by a change in page load time. The engineering team has already been notified because they own that metric. They have logged an action, and in two weeks you will know whether it worked. That closed loop does not exist in any BI platform.
- Dedicated infrastructure running entirely within your chosen cloud region. Your data never shares compute or storage with other customers. We support GCP, AWS, and Azure. Your security and infrastructure teams will have full visibility into the deployment architecture.
- Most enterprise customers are live within weeks, not months. The initial tree structure can be built in a working session with your leadership team. Data connections follow your existing integration patterns. We provide a dedicated solutions engineer for onboarding, and our API-first architecture means custom integrations are straightforward.
- Each department can have its own tree with its own structure, owners, and thresholds. Trees roll up to a consolidated organisational view. The marketing tree feeds into the revenue tree, which feeds into the P&L tree. Each team sees the detail they need. Leadership sees the full picture.
- KPI Tree includes full OKR support: set objectives, define key results, and track progress automatically. But OKRs live inside a persistent causal model that does not reset every 90 days. Your objectives attach to metrics in the tree. Your key results connect to the data. When the quarter ends, the understanding, the ownership, and the impact history remain. Some teams use KPI Tree as their OKR tool. Others use it alongside one. Either way, the metric tree outlasts every quarterly cycle.
Related guides
Deep dives into the frameworks and metrics that matter most for enterprise.
One model. Every metric. Named owners. Verified impact.
Connect your data stack, map the causal relationships between metrics across every department, and give your organisation the closed loop from insight to action to measurable outcome. Talk to our enterprise team.
