Chief Data Officer — Home-Care Division

The mandate

The division needs management teams to share one dependable explanation of where value is earned or lost. Product profitability is calculated at different levels of the hierarchy, promotion effects are separated from later returns and logistics, and formulation or pack changes can take months to appear consistently across technical, supply and financial records. Analysts spend substantial time reconciling results, yet important executive decisions still rely on estimates whose lineage is difficult to explain.

The Chief Data Officer will build the information accountability required to change that position. The remit includes enterprise data strategy, governance, master and reference data, data-product management, analytical engineering, information quality, metadata and responsible advanced analytics. Technology infrastructure remains with the CIO, functional executives own business processes and finance retains authority over statutory and management reporting. The CDO must establish where data ownership sits, provide products that support real decisions and make limitations visible before numbers become commitments.

This is a planned replacement with a deliberate change in emphasis. The board is not seeking a larger central warehouse or a catalogue celebrated for the number of entries it contains. It wants faster, traceable answers to margin questions and fewer reconciliations between functions. The CDO will be expected to stop analytical work that has no decision owner, even when the model is technically sophisticated.

Scope and operating context

Based onsite in Amsterdam, the role leads approximately 600 employees and material partners across the Netherlands and a broader international region. Direct and matrix teams include data governance, analytical engineering, data-product owners, data science, master-data specialists and regional analytics. Significant capacity sits inside finance, commercial, supply, research and technology functions; the CDO must create a federated system in which those experts retain domain context while meeting shared standards.

Home-care economics depend on relationships between formulation, ingredient, pack, manufacturing route, customer terms, promotion, order pattern and distribution path. Those relationships are not stable. A material substitution changes cost and perhaps product claims; a new pack alters case configuration and warehouse handling; a customer-specific promotion affects volume, returns and transport. Data products must preserve effective dates and lineage so leaders can understand which version of a product or assumption a result describes.

The division also buys retailer, panel and digital information under varying usage rights. Combining it with internal customer or consumer records requires contractual, privacy and competition discipline. The CDO will work with legal and privacy leaders to define permitted use and retention, ensuring commercial pressure does not convert licensed information into an uncontrolled enterprise asset.

First-year agenda

The opening one hundred days will focus on a small set of disputed margin decisions. The CDO will trace how product and customer profitability, promotion return, cost-to-serve, innovation economics and inventory exposure are currently produced. For each, the review will identify source systems, transformations, manual overrides, owners, timing and material uncertainties. This decision-led map will reveal where governance and engineering effort can change an outcome rather than merely improve documentation.

The executive will then define a margin-data architecture and ownership model. Core domains—product, formulation, material, customer, promotion, supplier, location and cost—will have accountable business owners, data stewards and quality thresholds appropriate to use. Shared identifiers and effective dating will allow technical, operational and financial views to reconcile without pretending that one hierarchy answers every purpose.

Several data products should reach active use during the first year. One may connect the gross-to-net waterfall with post-promotion returns and fulfilment cost; another may show the full economics and claims dependencies of a formulation or pack change; a third may identify margin leakage from small orders, special handling or volatile service. The final choices will follow the initial diagnostic. Each product must have a named executive consumer, a decision cadence and an adoption measure.

The CDO will also reset analytical model governance. Forecasts and optimisation tools must state the target, training period, assumptions, stability limits and human override. Where a price, promotion or assortment recommendation affects a customer or consumer materially, responsible executives need an intelligible explanation and a way to contest the input. Models that perform well in aggregate but fail in important categories or markets will not be approved silently.

By the end of twelve months, the executive committee should be able to review margin actions from a reconciled evidence base with known confidence. Manual reconciliation around priority decisions should decline, material product and customer changes should propagate more reliably, and a clear backlog should show why the next data investment outranks alternatives. Improvements must remain after central analysts withdraw.

Leadership responsibilities

The CDO will chair data ownership and prioritisation forums, but domain leaders will remain accountable for the meaning and quality of their information. The central team will supply standards, engineering, discoverability and assurance. Persistent quality failures will be addressed through process and role design, not endless downstream cleansing.

The executive will build an organisation that values adoption as highly as analytical craft. Product managers, engineers, scientists and stewards should spend time with account teams, factories, planners and finance users whose decisions they support. Vendor relationships will include access, portability and knowledge-transfer expectations so critical logic is not trapped in a proprietary service.

Board communication must be unusually clear. The CDO will explain where numbers reconcile, where they differ for legitimate reasons and where uncertainty changes a decision. They must resist demands for false precision and intervene when an attractive data story depends on an unrepresentative sample or a shifted definition.

Measures of success

The board will monitor adoption and decision use of priority data products, reconciliation time, quality at critical fields, lineage coverage, issue resolution and the proportion of domains with active business ownership. Engineering measures will include reliability, freshness and cost of data products. Catalogue volume, dashboard counts and raw model output will not be treated as success.

Business outcomes will include margin actions supported by traceable evidence, faster evaluation of pack and formulation choices, improved promotion learning, reduced leakage and greater confidence in cost-to-serve. Model performance will be segmented by relevant category and market. Benefits must be jointly owned by the commercial, supply or finance leader whose decision changed.

Candidate profile

Candidates should bring 18–22 years across enterprise data, analytics and information leadership in consumer goods, retail, manufacturing, life sciences or another product-rich environment. They must have led federated data ownership across functions and countries, with direct responsibility for production-grade data products rather than research or reporting alone.

The board will look for evidence of reconciling product, customer and cost information around a material value programme. Candidates should explain how effective dating, lineage or master-data choices altered a commercial or operational decision, and how they retired an analytical asset that users did not trust. Experience governing optimisation or machine-learning recommendations is expected.

The successful CDO will combine technical credibility, financial understanding and patient organisational influence. They must challenge executives who want instant certainty, but also challenge data teams that pursue perfection beyond the decision's value. Experience working within European privacy and data-sharing constraints is strongly preferred.

Compensation and appointment terms

Base compensation is expected to be EUR 285,000–390,000, plus annual incentive and long-term participation aligned with sustained enterprise value. Final positioning will reflect relevant scale, data-product leadership and current remuneration. Relocation support or treatment of forfeited awards will be assessed on an individual, documented basis.

Confidentiality

The client is undisclosed because the search involves leadership succession, sensitive margin measures and licensed customer data. Shortlisted candidates will receive progressively deeper information after identity, conflict and confidentiality review. Applications must exclude identifiable customer datasets, proprietary models and confidential profitability information from other employers.