Twelve versions of the same spreadsheet because nobody trusts the system. Decisions made on instinct because the data takes three days to pull and nobody believes it when it arrives. A new system commissioned to fix a data problem that is actually a governance problem. These are not IT issues. They are leadership ones. Starkhorn designs data strategies and governance frameworks that give mid-market and PE-backed organisations a single trusted view of their data, grounded in the commercial outcomes that actually matter. The person who designs it leads it. No junior consultants, no offshore delivery team.
In most mid-market organisations, data is fragmented across dozens of disconnected systems. Finance works from one version of revenue, operations from another. Nobody owns data quality. The same customer appears in five places with five different addresses.
The board makes decisions on data nobody fully trusts, or avoids making them at all. And every quarter, the gap between the data the business needs and the data it actually has widens. Starkhorn brings a commercial data strategy perspective built specifically for organisations that need data to work as a business asset.
Every assessment, every recommendation, and every framework is grounded in named commercial outcomes, not theoretical best practice.
Served as CIO and CISO at Jardine Motors Group through two major M&A transactions (Lithia and Pendragon) totalling over GBP 700m.
Led the design and implementation of an Azure Data Lake providing a single view of vehicle stock across hundreds of sites. Identified GBP 3.2M in inventory savings in the first year of operation.
Established data governance policies and ownership frameworks that passed FCA and SMCR regulatory review without a single finding.
Served as interim Group Technology Director at VetPartners, a BC Partners-backed veterinary group with GBP 1.2bn turnover, 14,000 staff, and 850+ sites across nine countries.
Led group-wide data asset mapping across a complex, multi-country estate. Established data quality baselines for ERP and clinical systems required for post-acquisition integration planning.
Current fractional Associate Director of IT at Alzheimer’s Society, responsible for protecting sensitive beneficiary and donor data across a major UK charity.
Established data governance and access controls that give trustees clear assurance on how data is handled, shared, and secured across the organisation.
The first step in every data strategy engagement.
Within the opening weeks, we map your data assets, identify where data is fragmented or untrusted, assess governance accountability, evaluate integration architecture, and deliver a board-ready report with a prioritised roadmap.
This assessment becomes the foundation for the strategy: which data problems to fix first, what commercial outcome each fix enables, and what governance structure will keep data quality from degrading again.
Not a technology audit.
A commercial assessment that identifies specific data quality issues, governance gaps, and integration failures, all presented in plain language with named commercial impact.
Most organisations discover that 30 to 50% of their data problems are governance and ownership issues, not technology ones. We find them, quantify them, and show you how to fix them.
In the first 100 days post-acquisition, a data strategy assessment answers the critical question: what data does the business actually have and can it be trusted?
Which systems have clean data. Which have known quality problems.
Where the integration dependencies are. What the data governance gaps mean for the value creation plan.
Organisations that invest in AI without first sorting out data governance almost always find the outputs cannot be trusted, because the underlying data is inconsistent, ungoverned, or poorly labelled.
Starkhorn designs data strategies with AI readiness built in from the start, so the investment in AI actually delivers. Sequence matters: data first, then AI.
Every finding framed in commercial impact: revenue recovered, cost avoided, compliance achieved, and decision quality improved. RAG-scored across data quality, governance, integration, and commercial value dimensions, with a prioritised roadmap at 30 days, 90 days, and 12 months.
Presented to your board in person, not emailed as a PDF.
Gartner estimates poor data quality costs organisations an average of $12.9 million per year in hidden operational costs (Gartner, 2021): duplicate effort, wrong decisions, manual reconciliation, and failed automation projects that depended on data that was not ready. For UK mid-market businesses, the impact is felt in every finance close, every operational report, and every technology investment decision made without a reliable data foundation.
The organisations that extract value from AI, automation, and digital investment are the ones that sorted out their data foundation first.
Every month without a data governance framework is a month where quality degrades further and the cost of fixing it grows.
A single view of your key business data, with clear ownership, consistent definitions, and governance that keeps quality from degrading. The foundation for every downstream commercial and technology decision.
Data governance that is documented and then ignored is not governance. We design frameworks that are practical, specific to your organisation, and adopted by the people who need to own data quality day to day, not just signed off by IT.
Integration architecture assessed against your actual business requirements: what data needs to move where, how reliably, and at what latency. No over-engineered data platforms for a 500-person business. No under-invested integration that breaks every quarter.
Every data strategy engagement is anchored to named commercial outcomes. Not theoretical best practice. Named outcomes with named accountability. The GBP 3.2M Jardine inventory saving was not accidental: it was the product of a data strategy designed to find that value.
The Data Governance Health Check
A structured assessment of your data governance maturity across four dimensions. Completed in under two weeks. Gives your board and investors a clear picture of where data quality, ownership, and compliance stand before committing to a larger strategy engagement.
Data asset inventory and quality assessment across core systems
Governance accountability and ownership review
Board-ready report with commercial impact and prioritised roadmap
Organisations that cannot give their board a clear answer on data quality and governance are carrying a risk that grows every quarter. We find what is there, what is missing, and what it is costing you.
“The GBP 3.2M inventory saving came from having a single trusted view of stock for the first time. That is what a data strategy actually delivers: not a platform, not a dashboard, but a decision the business could not make before.” Daniel Jacobs, Founder, Starkhorn
The Technology Health Check includes data and information management as one of its eight assessment dimensions. It tells you where your data governance gaps sit before you commit to a full strategy engagement.
Eight dimensions. Ten minutes. Immediate results. No obligation.
If you are facing an immediate data governance problem, a regulatory review that requires evidence of data management, or a post-acquisition data mapping exercise that needs to start this week, Starkhorn can engage quickly. Daniel Jacobs can typically be briefed within 24 hours.
This is not a sales call. It is a genuine assessment of your data situation and what the right first steps are.
Available for mid-market, PE-backed, and not-for-profit organisations.
Whether you are dealing with fragmented data across a multi-system estate, preparing for an M&A transaction, building the data foundation for AI adoption, or getting governance evidence-ready for a regulatory review: start with a conversation.
The Starkhorn Data Strategy Framework
Most data strategy engagements start with technology. Starkhorn starts with the business question: what decisions does this organisation need to make better, and what data would make that possible?
| Dimension | What it covers | Why it matters |
|---|---|---|
| 1. Data asset inventory and ownership | What data the organisation holds, where it lives, who owns it, and whether it is trustworthy | You cannot govern or monetise data you cannot find or trust |
| 2. Data governance and accountability | Policies, roles, and decision rights that govern how data is created, stored, shared, and used | Without accountability, data quality degrades and compliance exposure grows |
| 3. Data architecture and integration | How data flows between systems, how it is integrated across the estate, and how reliable that flow is | Fragmented architecture means the same data exists in twelve places and none of them agree |
| 4. Data value and outcomes | The commercial outcomes the data strategy is designed to enable, from operational efficiency to new revenue | A data strategy without a commercial output is a compliance project, not a business asset |
Proof
Named outcomes from named engagements. These are not case study summaries.
| Organisation | Challenge | Outcome |
|---|---|---|
| Jardine Motors Group (GBP 2bn) | Fragmented vehicle inventory data across hundreds of sites and two major M&A transactions | Azure Data Lake providing single view of stock; GBP 3.2M inventory saving identified in first year |
| VetPartners (GBP 1.2bn, BC Partners) | Data asset mapping required across 9 countries and 850+ sites post-acquisition | Group-wide data inventory and governance framework established; data quality baselines set for ERP and clinical systems |
Common questions
What is a data strategy and why does a mid-market business need one?
A data strategy is the plan that determines how an organisation creates, manages, and uses its data as a business asset. Mid-market businesses typically reach a point where data is fragmented across multiple systems, inconsistent, and not trusted by the people who need to make decisions with it. Without a strategy, the default is that everyone builds their own spreadsheet and the organisation makes decisions on different numbers.
How does data strategy relate to AI readiness?
AI requires clean, governed, accessible data. Organisations that invest in AI without first sorting out data governance almost always find the AI produces outputs nobody trusts, because the data going in is inconsistent or poorly labelled. A data strategy is the prerequisite for sustainable AI adoption. Starkhorn works on both: data strategy first, then AI readiness.
What is the CDO gap and how does it affect mid-market businesses?
Most mid-market organisations have no Chief Data Officer. Data governance by default lands with the CIO, who often does not have dedicated resource to own it properly. The CDO gap means data quality degrades quietly, compliance exposure builds, and the business misses the commercial value sitting in its own systems. A fractional CIO with data strategy experience closes that gap without requiring a permanent hire.
How does data strategy work in a PE-backed acquisition context?
PE acquisitions often surface a data problem fast: the acquired business has no reliable data on its own assets, customers, or costs. This makes the integration plan harder and delays value creation. Starkhorn leads data asset mapping and governance design as part of the first-100-days technology assessment, giving the investor and management team a trustworthy picture of what they actually own.
How long does a data strategy engagement take?
A data strategy engagement runs six to twelve weeks for the strategy and governance design phase: two to three weeks of discovery and data asset mapping, two to three weeks of architecture and integration review, two to four weeks of framework design and board presentation. Implementation is a separate phase, typically led fractionally over six to eighteen months.
First step
A 30-minute discovery call covers what you have, what is missing, and what a data strategy engagement would focus on. No obligation and no pitch deck.
Book a discovery callThe Technology Health Check includes data and information management as one of eight dimensions. Ten minutes to a clearer picture of where your data governance stands.
A 30-minute call about your data situation. We will tell you honestly what the priority is and what an engagement would focus on. No pitch. No obligation.
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