[Whitepaper title]: [Subtitle that states the benefit or finding]

Whitepaper template for an authoritative, evidence-based report that explains a problem, analyses it and argues for an approach. Based on common practice in B2B, technical and policy publishing: executive summary, problem, context, analysis, proposed approach, evidence, implementation, risks, conclusion and references. Replace every [bracketed] value and every line marked Example.

Document control

Approvals

Revision history

Contents

1. Executive summary
2. Introduction and problem
3. Background and market context
4. Analysis
5. Proposed approach
6. Evidence and case examples
7. Implementation considerations
8. Risks and limitations
9. Conclusion and call to action
10. About the authors
11. References
12. Appendices

1. Executive summary

The problem. [One or two sentences that name who is affected and the cost of doing nothing.]

What we found. [The two or three findings that carry the argument, each with a number and source.]

What we recommend. [The approach in one paragraph.]

Expected outcome. [Measurable benefit and time frame.]

Example: Mid-size banks spend an average of 31% of their data engineering time reconciling the same customer records across systems (survey of 212 banks, section 6.1). Our analysis shows that most of this effort comes from three root causes that a governed "customer golden record" removes. Banks that adopted this approach cut reconciliation effort by 40 to 60% within 12 months and passed regulatory data-quality reviews with no major findings.

Key takeaways:

• [Takeaway 1 with a number]
• [Takeaway 2]
• [Takeaway 3]

2. Introduction and problem

2.1 The problem

[Describe the problem in concrete terms, with at least one quantified impact: cost, risk, time, missed revenue, regulatory exposure.]

2.2 Why it matters now

[Trends, regulation, technology changes or market events that make the problem urgent this year.]

Example: New supervisory guidance effective YYYY-MM-DD requires banks to show lineage for every customer data element used in risk reports.

2.3 Audience

[Who the paper is written for, what they already know, and what decision or action it should help them take.]

2.4 Scope and question

This paper answers: [the central question]. It covers [scope] and does not cover [out of scope]. Section 3 sets out the context, section 4 analyses root causes, section 5 proposes an approach, and sections 6 to 8 present evidence, implementation guidance and risks.

3. Background and market context

3.1 Key concepts and definitions

3.2 Market and industry context

[Market size, adoption rates, typical spending, regulatory landscape, with sources.]

3.3 Current approaches and their limits

4. Analysis

4.1 Method

[How you gathered and analysed evidence: sample, period, sources, analysis technique.]

Example: Online survey of 212 data leaders at banks with USD 5 to 50 billion in assets, fielded YYYY-MM to YYYY-MM; 18 follow-up interviews; analysis of 40 public regulatory findings.

4.2 Findings

[Present each finding as a heading-style sentence followed by the evidence.]

Finding 1: [Statement]. [Evidence and explanation.]

Finding 2: [Statement]. [Evidence and explanation.]

Finding 3: [Statement]. [Evidence and explanation.]

Table 1 summarises the root causes and their share of the problem.

Table 1. [Caption]. Source: [source].

4.3 Implications

[What the findings mean for the reader: which assumptions are wrong, which costs are hidden, what a solution must therefore do.]

5. Proposed approach

5.1 Principles

1. [Principle linked to a root cause.]
2. [Principle.]
3. [Principle.]

5.2 How it works

[Explain the approach step by step, with the main components and how they interact.]

The diagram below shows the main components and data flow.

5.3 How it addresses each root cause

6. Evidence and case examples

6.1 Quantitative evidence

[Survey results, benchmarks or models that support the approach.]

When a benefit is modelled, show the calculation so readers can test it with their own inputs, for example:

Example: $20 \times 120{,}000 \times 0.31 \times 0.5 = 372{,}000$ USD per year.

6.2 Case example: [Organisation or anonymised description]

6.3 Case example: [Second case]

[Same structure as 6.2, ideally a different context to show the approach generalises.]

6.4 What the evidence does and does not show

[Summarise the strength of the evidence in plain words. Separate results that were measured from results that were modelled or reported by participants, and note what would change your conclusion.]

Example: Measured results come from two organisations and a survey of 212; the 40 to 60% reduction range is based on those two cases and the survey's self-reported estimates. A controlled comparison across more banks would strengthen the claim.

7. Implementation considerations

7.1 Phased roadmap

7.2 Prerequisites and roles

Before starting, the organisation needs the following in place:

• Executive sponsor: [role], who owns the business case and removes blockers across departments.
• Data owners and stewards for each domain, with time allocated in their objectives rather than added on top of existing work.
• [Technical prerequisites, for example access to source system extracts, a target platform, identity and access management.]
• [Governance prerequisites, for example an agreed data quality policy and an escalation route for conflicting definitions.]

7.3 Cost drivers and success measures

[What drives cost, and the KPIs to track with baseline and target.]

7.4 Common pitfalls

1. [Pitfall and how to avoid it.]
2. Example: Starting with the hardest domain. Choose a domain with a visible business owner and clean enough sources to show results in one quarter.
3. Example: Treating the project as a technology purchase. Most of the value comes from agreed definitions and stewardship, not the tool.

8. Risks and limitations

Limitations of this paper: [sample, period, self-reported data, conflicts of interest].

9. Conclusion and call to action

[Summary of the problem, the key findings and the recommended approach.]

Next step: [One concrete action, for example "Download the assessment checklist in Appendix A and score your current state", or "Book a 30-minute data maturity review at [URL]".]

10. About the authors

[Author name], [Title], [Organisation]. [Two or three sentences on relevant expertise.]

[Author name], [Title], [Organisation]. [Bio.]

About [Organisation]. [One paragraph.] Contact: [email or URL].

Disclosure: [For example, "The authors' employer sells data management software; the survey was conducted independently by [firm]."]

11. References

Citation style: [APA 7].

1. [Author, A. (Year). Title. Publisher. URL or DOI]
2. [Organisation. (Year). Report title. URL (accessed YYYY-MM-DD)]
3. Example: [Regulator]. (2025). Supervisory guidance on data lineage for risk reporting. [URL] (accessed YYYY-MM-DD)

12. Appendices

Appendix A: [Assessment checklist or methodology detail]

[Content that lets readers apply the paper to their own situation, for example a self-assessment with scoring.]

Appendix B: Glossary

Appendix C: Pre-publication checklist

• The executive summary matches the body and contains no new claims.
• Every number has a source in section 11 or in the paper's own data.
• Figures and tables are numbered, captioned and referenced in the text.
• Customer names, quotes and logos have written permission.
• Legal or compliance review is recorded under Approvals.
• Alternative text is written for every figure, and the exported PDF is tagged for accessibility.
• The call to action link works and tracks only what the privacy notice allows.

Standard and licence note

Based on common industry practice for business, technical and policy whitepapers. Original text written for this collection; example figures, organisations and findings are fictional. Template licence: MIT.