Clarke Analytics

At Clarke Analytics, we don’t just analyse data. We help you answer your most critical business questions, using a proven and prioritised methodology grounded in the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework. Our approach is trusted by regulated and data-intensive industries, including life sciences, manufacturing, and retail.

We start with your business goals – not the data. Through structured discovery workshops, we help your team clearly articulate the most pressing challenges and opportunities. Using CRISP-DM, we guide your organisation through a focused, iterative process that links business understanding to data understanding, model development, evaluation, and deployment.

Some of our consulting services are specifically designed for those difficult early phases of analytic solution development and our methodology takes account of some specific attributes of data analytics projects.

What sets our CRISP-DM execution apart?

• Prioritised Insight Delivery: Our framework ensures early and ongoing alignment of analytics efforts with high-value business questions.
• Rapid Value Identification: Through Analytics Innovation Labs and structured maturity assessments, we surface quick wins and long-term strategies backed by ROI models.
• Validated Statistical Rigor: In domains like medical devices and pharma, we bring advanced analytics, including multivariate modelling and regulatory-compliant statistical reviews, to ensure robustness and repeatability​​.
• Real Business Outcomes: From reducing process variability and production scrap, to optimising supply chain cash flow and customer satisfaction, our clients achieve tangible, quantifiable improvements​.

The benefits for you is combining deep domain knowledge, robust statistical techniques, with the structured flow of CRISP-DM. Clarke Analytics helps you cut through data noise and find the answers that matter most, efficiently, transparently, and with measurable results.

From Gut Feel to Evidence: Integrating CRISP-DM with Lean Sigma DMAIC for Smarter Decisions

At Clarke Analytics, we combine the structured power of CRISP-DM with the proven Lean Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology to deliver data-backed continuous improvement. This fusion enables you to move beyond intuition-led problem solving, introducing statistically validated hypothesis testing into the heart of operational excellence.

While traditional DMAIC initiatives rely heavily on subject matter expertise to frame hypotheses, our hybrid approach anchors those insights in data from the outset. Using CRISP-DM’s rigorous data understanding and preparation phases, we uncover hidden patterns, outliers, and root causes that may not be visible through process maps alone.

Our method enhances every stage of DMAIC:

• Define & Measure: Business objectives are translated into measurable analytics questions, informed by structured data profiling and maturity assessments​​.
• Analyse: We use advanced statistical modelling, from ANOVA and regression to multivariate factor analysis, to rigorously test process hypotheses and isolate key drivers​​.
• Improve & Control: Predictive models and scenario simulations support proactive decision-making, while dashboards and control charts enable sustained visibility and governance.

This integrated approach delivers faster root cause identification, greater confidence in solution selection, and stronger alignment between SME judgment and empirical evidence. The benefits for you are more targeted interventions, faster improvement cycles, and lasting business impact across quality, efficiency, and customer satisfaction metrics.