Ask the Expert: How does O’Neill stay agile in a seasonal business and what does data-driven planning look like in practice?
To explore how seasonality, frequent drops and changing demand impact daily decision-making, we turned to Senem Erdogan from O’Neill. She shares how O’Neill approaches agile, data-driven planning and what it takes to make replenishment work in real operations.
Do you want to know her insights? Watch the full interview below!
In this interview, Senem Erdogan, Head of Merchandising at O’Neill, discusses how the brand manages strong seasonality, demand volatility and operational complexity through agile, data-driven planning, supported by its partnership with Chainbalance.
Senem’s team is responsible for product merchandising, merchandise planning and demand planning. They oversee the entire lifecycle of product and stock management across channels. O’Neill’s identity and operations are built around two major seasons: summer and winter, with core strengths in swimwear and snowwear, complemented by head-to-toe assortments.
A central theme of the conversation is seasonality. While O’Neill operates with two main seasonal collections, the business is also driven by frequent product drops, replenishment cycles and core assortments. This combination creates complexity: the brand must ensure the right stock is available at the right time, without ending up with excess inventory when seasons end or demand shifts unexpectedly.
Senem highlights that forecasting accuracy is the biggest challenge facing the industry. Before adopting Chainbalance, O’Neill relied heavily on manual Excel-based planning and verbal input from store teams, which led to reactive decision-making. Initial allocations and replenishments often lagged behind real demand, increasing the risk of both overstock and understock. With Chainbalance, replenishment decisions are now system-driven, using data to determine when to push inventory, slow replenishment or adjust stock levels. This shift significantly reduced reactivity and helped establish a more consistent planning cadence.
Another major challenge discussed is the gap between rapid changes in customer demand and slower operational response times, especially during peak periods. Promotional items, weather-sensitive categories and holiday-driven demand were particularly difficult to manage using traditional methods. These pressures affected not only planning teams, but also logistics and retail operations, creating stress across the organization. By improving live sales signal integration, introducing dynamic parameter updates and enabling exception-based alerts, O’Neill shortened reaction times and reduced stock-outs during critical sales periods.
Agility emerges as a key success factor for O’Neill. Senem emphasizes that, for a performance-driven sports brand, agility is essential due to unpredictable weather, regional differences between northern and southern markets, and fast-changing consumer trends. However, agility alone is not enough. Without solid data and planning foundation, agility becomes purely reactive. Chainbalance provides the forecasting base, real-time visibility and dynamic parameters that allow O’Neill to move from chasing demand to actively shaping it.
Addressing multi-channel complexity, including full-price retail, outlets and new marketplaces: each channel behaves differently, with unique demand patterns and peaks. Chainbalance enables O’Neill to allocate inventory intelligently across channels, balancing growth while protecting full-price performance. O’Neill is currently seeing double-digit growth, both month-over-month and year-over-year, which has encouraged expansion into marketplaces such as Zalando, Wehkamp and About You.
Looking ahead, Senem views Chainbalance AI as a crucial enabler of future growth. She emphasizes the importance of a true partnership, where both companies grow together, actively exchange ideas and co-develop solutions. For O’Neill, this collaborative, forward-looking approach ensures they remain proactive, scalable and resilient as data volumes, channels and business complexity continue to increase.