Overview
FMCG and CPG businesses operate in a highly competitive market where consumer preferences can change quickly, margins are under pressure and getting the right products to the right place at the right time is critical.
Data, analytics and AI are critical to how businesses build a competitive advantage in this environment, helping improve demand forecasting, strengthen supply chain visibility, understand consumer behaviour and support faster commercial decision-making. With the right data strategy and foundations in place, FMCG and CPG organisations can respond more effectively to market change, optimise inventory and operations, and identify new opportunities for growth.
At Cynozure, we help FMCG and CPG companies use data, analytics and AI to improve demand planning, deepen consumer insight and make better decisions across products, categories and supply chains. Our approach starts with the commercial outcome,not the technology. We align business and data leaders around the highest-value opportunities, build the strategy and foundations, deliver data and decision products into real workflows, and transfer the capabilities needed to sustain and scale results. This end-to-end, outcome-led approach helps close the gap between data investment and measurable commercial value.
Here’s how Cynozure can help FMCG and CPG companies thrive
We help FMCG and CPG companies improve commercial and operational decision-making, from understanding consumers and forecasting demand to managing supply and bringing products to market. We combine sector-relevant use cases with value-led prioritisation, pragmatic delivery and capability building, so solutions are adopted by teams and designed to keep delivering value after the initial engagement
Supply chain & demand forecasting
We help you use data and analytics to forecast demand more accurately, optimise inventory and improve visibility across your supply chain. We connect forecasting models to planning workflows and frontline decisions, helping teams act on insight rather than producing analysis in isolation. This can help reduce disruption, improve product availability and make more effective use of stock and resources.
Better forecasting and inventory decisions can help improve forecast accuracy by 3–8 percentage points, reduce inventory holding by 5–15% and cut stock-outs or lost sales by 5–20%. They can also support a 5–15% reduction in waste and obsolescence and improve on-shelf availability by 1–3 percentage points.*
Consumer insights
We help you build a clearer understanding of consumer and shopper behaviour, preferences and purchasing patterns. We bring fragmented data together around priority decisions and put reusable insight products into the hands of commercial teams. These insights can inform decisions across marketing, products, promotions and channels, helping you respond more effectively as needs and behaviours change.
Better use of customer, campaign and commercial data can help improve promotion ROI by 3–10%, campaign conversion or response by 5–15% and speed to insight by 20–40%. It can also support a 1–3 percentage-point improvement in customer or segment profitability and reduce research and analysis effort by 10–25%.*
Product & category innovation
Changing consumer needs create opportunities for new products, categories and propositions. We help you identify emerging trends, prioritise opportunities by value and feasibility, and turn consumer and market data into evidence that supports faster, more informed product decisions. By combining commercial framing with rapid delivery, we help teams test, learn and scale without waiting for a perfect enterprise solution.
Better use of data across innovation and product development can help make concept-to-launch cycles 10–25% faster and opportunity identification and validation 20–40% faster. It can also support a 5–15% improvement in innovation success, a 1–3 percentage-point increase in revenue from new products and a 10–20% reduction in test-and-learn costs.*
Data strategy & value creation
We help you build the data strategy, capabilities and ways of working needed to use data and AI effectively across your organisation. Rather than producing a strategy that sits on a shelf, we create a value-led roadmap, mobilise priority use cases and build ownership across business, data and technology teams. Our collaborative approach transfers knowledge and capability, reducing long-term dependency while helping successful solutions scale. By focusing investment around clear business opportunities, we help turn data and AI into measurable business value.
Stronger data platforms and delivery practices can help move ideas into deployed use cases 20–40% faster, increase active adoption of data products by 10–25 percentage points and reduce duplicated data or reporting effort by 10–25%. They can also support a 10–20 percentage-point increase in use cases achieving agreed value targets and reduce avoidable platform and delivery costs by 5–15%.*
ESG, sustainability & responsible data
For CPG companies, ESG performance increasingly depends on trusted data across complex products, suppliers, operations and routes to market. We help you create the data foundations, governance and decision tools needed to measure product and operational footprints, improve supplier and materials traceability, identify packaging, waste, water and emissions hotspots, and support credible internal and external reporting. We also embed responsible data and AI practices so that new capabilities are transparent, governed and aligned with business and societal outcomes.
Better use of ESG and sustainability data can help improve Scope 1, 2 and 3 data coverage and quality by 10–25 percentage points, make ESG reporting cycles 20–40% faster and reduce manual data preparation by 20–40%. It can also support stronger supplier or material traceability and a 5–15% reduction in targeted packaging, waste, water or emissions intensity.*
* The indicative benefits above are opportunity guides, not guarantees, and would be validated against your baseline, operating context and chosen use cases during discovery.