Our Beliefs
With extensive experience across diverse retail environments, OneHive shares its convictions and proven practices from the earliest project stages through to delivery.
Managing the in store offer is a strategic exercise that shapes the entire commercial ecosystem. Our expertise has helped identify the fundamentals of an effective assortment: robust store segmentation, high quality product taxonomy and dynamic offer animation across commercial milestones.
Our approach combines analytical rigor with operational pragmatism to design solutions that genuinely fit your business. From store clustering to calculating fixture quantities, our methodology transforms buying and assortment planning into a durable and measurable competitive advantage. This positioning strengthens your ability to build a coherent assortment plan and size buying volumes accurately.
Benefits
Tangible results delivered for our clients
Implementing an assortment and buying management model allows merchandising teams to reduce time spent on low value tasks such as data collection and cleaning, which become fully automated. Effort is redirected toward analysis, strategy and informed decisions that generate measurable gains.
Clear results observed among our clients:
- Improved assortment efficiency measured through sales per item included in the offer
- Stronger brand image in store with a coherent and diversified presentation
- Higher sell through thanks to more precise, quantified buying estimates
- In season sales uplift enabled by targeted assortment adjustments
- Productivity gains across merchandising teams
These improvements directly reinforce the performance of the assortment plan and stabilise buying volumes.
The foundations of reliable assortment planning
Master Data and Transactional Foundations
We support you early in the project to secure essential prerequisites.
- Product and store master data: These master data structures are critical to the process, and their accuracy is especially important during buying cycles. Our solutions connect easily to your PLM and support high frequency data exchanges. The technical architecture between our application and your PLM remains flexible and tailored to your context.
- Source data availability and quality: Sales histories, stock data and production delivery information feed quantitative analyses, alerts and synthesis views. Ensuring the reliability of these data sources is crucial, as it enables automated usage within the tool.
These data foundations secure the accuracy of the assortment plan, clustering logic and buying volume calculations.
Store Clustering
After an initial scoping phase to understand your specificities, we define an optimised methodology for grouping stores.
A wide range of approaches is possible. Clustering can be managed manually, leveraging your teams’ qualitative insight supported by quantitative analyses, or automated through rule based modelling using parameters such as size, stock constraints, revenue, customer profile, seasonality or geography.
We can also integrate recommendations generated by AI models that create dynamic links between stores and products, moving beyond traditional clustering frameworks. This segmentation strengthens the relevance of assortment proposals and sharpens buying quantities by zone.
Operational Onboarding
Our project approach aims for a secure deployment that balances our recommendations with your operational feedback. We involve key users at every stage to validate business rules, user journeys and specific use cases.
Flexible and intuitive interfaces support fast adoption and make the solution accessible to all end users. This continuous involvement strengthens ownership of the assortment model and ensures high quality buying decisions.
MVP Approach and Phased Deployment
We recommend an MVP approach with a first functional model delivered in three to four months, followed by iterative enhancements and analytical reports. We also favour progressive deployment through pilot scopes and structured change management.
In international projects, pilot based rollouts secure adoption and allow fine tuning before the final launch. Dedicated synthesis views and targeted features help test and validate key indicators under real conditions, aligned with current policies.
This methodology accelerates the value delivered by the assortment plan and strengthens the accuracy of buying quantities from the very first seasons.
Solutions to Assortment and Buying Challenges
Beyond these core foundations, we address your concrete operational challenges:
- Omnichannel management: Integration of web strategy, inclusion of Wholesale within assortment and buying processes.
- Lifecycle management: Handling of launches and phase outs, store openings and closures.
- Collaboration and process connectivity: Assortment projection, export to Supply processes, alignment with production after buying sessions and in season performance tracking.
- Operational constraints: Consideration of shipping, receiving and storage constraints following buying decisions, with synthesis views for Retail and Logistics teams.
- Central and regional coordination: Structured workflows for validation, communication and collaboration across teams during the entire cycle.
- Strategic indicators: Implementation of key metrics such as OTB and budget tracking, along with collection plans aligned with business expectations.
These levers enable better dimensioned assortments and more accurate buying quantities.
Technical topics and innovation
Throughout the project, we work closely with your Data teams to address key topics such as data standardisation, automated interfaces, integration controls, solution robustness, performance and volume management.
With our partner IRIS by Argon and Co, we extend these capabilities with AI driven analyses and recommendations. These include:
- intelligent store and product clustering,
- product benchmarking from images and attributes,
- support for forecasting and estimating sales potential for new items.
These innovations sharpen clustering accuracy and improve the precision required for assortment planning and buying volume calculations.
