Marshall Tech
workflows and automationData HygieneAutomationProcess Design

It's 10x cheaper to prevent dirty data than to clean it after the fact. Validation at the point of entry: required fields, format masks, dropdowns instead of free text, automatic deduplication on create. Prevention over remediation.

On data quality management strategy

Nick Hugh

Founder, AI Expert & Fractional CTO, Marshall Tech

Nick Hugh, AI Expert & Fractional CTO at Marshall Tech, Sydney

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Insight

Data Hygiene Guide: Getting Your Data AI-Ready

Data hygiene is the practice of ensuring your business data is accurate, consistent, complete, and accessible. It's the prerequisite for AI implementation, reliable automation, and trustworthy reporting. Businesses with poor data hygiene waste 20–30% of employee time on manual data wrangling and get unreliable results from any AI or automation tools they deploy.

Updated 26 Feb 2026

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Workflows & Automation

Marshall Tech builds custom workflows, APIs, and automation for Australian businesses with manual handoffs, broken connectors, or duplicated data. We map the process, design the integration layer, and ship monitored automation that reduces admin load, improves reliability, and removes vendor lock-in from critical operations.

Updated 26 Feb 2026

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Updated 9 Apr 2026

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How to Estimate Automation ROI: A Practical Framework

Automation ROI is calculated by comparing the cost of automation (build + maintain) against the value of time saved, errors eliminated, and throughput gained. A well-scoped automation project typically pays for itself in 2–4 months. The key is targeting processes that are high-volume, rule-based, and currently handled by expensive human time.

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On data quality as a prerequisite for AI

Before you invest in AI, automation, or a new CRM, answer this: is your data clean enough to be useful? If your team maintains shadow spreadsheets, the answer is no. Fix data first, then automate.

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On common RevOps implementation mistakes

Treating RevOps as a technology project is the number one failure mode. Buying a RevOps platform without changing how teams work together just creates a more expensive version of the same problem. Start with process alignment, then automate.

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