Management consulting
The best platform fails on unclear responsibilities. That is why, alongside the technology, we build the organization behind it: target operating model, governance structures, roles, and enablement. So that analytics does not remain a project, but becomes an operating model.
01 · Symptoms
The most common problems we encounter in large enterprises have no technical root cause. They arise from missing structures, and can only be solved there.
Controlling calculates net, sales calculates gross, marketing counts leads. The board meeting starts with a debate about numbers instead of decisions. That is not a technology problem but a governance problem: there is no binding authority over definitions.
Every request runs through an overloaded BI team, departments wait weeks for a dashboard, and build shadow solutions in Excel in the meantime. More tools will not fix this; an operating model with a clear division of labor between the center and the business will.
The analytics project is signed off, the project team moves on, and no one is responsible for maintenance, further development, and adoption. Without roles, a budget model, and operational ownership, every platform decays. Organization is the answer to what happens after go-live.
02 · Operating Model
More important than any tool is how analytics is anchored in the company: Who decides, who delivers, who operates? We design your operating model along proven patterns, and adapt it to size, culture, and regulation.
A central analytics team owns platform, standards, and delivery. The model is strong on consistency and efficiency, but beyond a certain size the center becomes a bottleneck and time-to-insight increases.
Each business unit runs its own team. That accelerates delivery, but without shared standards it leads to unit-specific definitions, unit-specific tools, and conflicting truths in management reporting.
A central competence center sets standards, runs the platform, and safeguards governance; decentralized spokes in the business units deliver fast. For most larger organizations the most sustainable model, provided mandate and interfaces are cleanly defined.
In the operating model we define: reporting line and mandate (who does the CDAO report to?), boards and decision paths, role profiles, demand management, and the split of capacity between operations (run) and development (change). The derivation (maturity assessment, evaluation, roadmap) is covered on our Analytics & AI Strategy page. This page is about design and implementation.
Governance rarely fails on the concept: it fails on anchoring. We establish structures that accelerate decisions instead of preventing them.
An analytics board that prioritizes and resolves conflicts. Data owner rounds that approve definitions. Clear escalation paths for platform and budget questions. We keep boards lean enough to decide, not to administer.
A binding KPI catalog from board level to working level: one definition per KPI, one owner, one approval process. Certified reports carry a visible seal of approval, everything else is work in progress.
Every data domain gets an owner with a mandate, stewards for daily operations, and a RACI matrix that reflects real decision-making power, not wishful thinking. The data-side deep dive is on our Data Governance page.
04 · CoE & Roles
Building an organization means staffing structures, introducing processes, and handing over responsibility. We support you from mandate to well-rehearsed routine.
We build analytics competence centers: service catalog, staffing, interfaces to IT and business units, service levels. The mandate is decisive: a CoE without authority remains a discussion circle.
Data engineer, analytics engineer, BI developer, data steward, analytics product owner: we define profiles, seniority levels, and development paths, as the basis for job postings, internal staffing, and targeted upskilling.
A transparent process from request to delivery: structured intake, evaluation by business value, capacity management between run and change. Business units always know where their request stands.
05 · Advisory & Enablement
Organizational questions are leadership questions. We act as a sparring partner to decision-makers, and make sure the change reaches employees.
Reporting lines, the split between IT and business, degree of centralization, budget and charging models: we bring experience from large corporate organizations, as a sparring partner, not a slide supplier.
Whether reorganization, CoE founding, or a new operating model: we deliver papers with options, costs, risks, and a clear recommendation, tailored to the executive board, supervisory board, or IT steering committee.
Training paths per audience, champions in the business units, a community of practice, and adoption KPIs such as active users, time-to-insight, and self-service ratio that guide the enablement. Interlocked with our BI and AI training programs.
We have built both sides: data models and boards, pipelines and processes. That is why we never recommend an organization that fails on technical reality, or an architecture no one can operate.
Matrix organization, works council, budget cycles, IT governance: our models account for the reality of large companies, including how change actually gets decided and carried there.
Central, decentralized, or hub & spoke is not a question of belief but a function of size, maturity, and regulation. We fit the model to your company, not the other way around.
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