Big LotsがTotal Retail誌の「2020年トップ・オムニチャネル・リテーラー・レポート」で第1位に選ばれました

Recommendation: Build a unified omnichannel operation that blends online orders with in-store fulfillment and curbside pickup to capitalize on Big Lots’ No. 1 standing in Total Retail’s 2020 Top Omnichannel Retailers Report.

Approach: Implement two core strategies in operation improvement: first, expand テクノロジー-enabled fulfillment to improve accuracy and speed; second, standardize certifications across partners to reduce コスト and risk. Prior results were driven by data-informed decisions and close collaboration across channels.

で january, forecasts point to growing demand for essentials and snacks, with online orders turning into quick pickups and rapid replenishment across stores.

レバレッジ informa data and dumont analytics to sharpen inventory planning, align assortments with shopper momentum, and reduce out-of-stock events that could affect margins.

Maintain momentum by tracking コスト per fulfilled order, speeding up cycles, and enforcing process certifications that guarantee quality across all channels. This approach helps them reduce friction for customers.

That momentum will be supported by a second wave of growth, stronger テクノロジー adoption, improved operation discipline, and smarter forecasts that could sustain omnichannel leadership into the next season.

Practical inventory management techniques that powered Big Lots’ omnichannel leadership

Start with a unified, cloud-based inventory platform that consolidates store, distribution center, and online stock with real-time updates. Install RFID on high-demand items and pair it with wearables for store teams to scan shelves in seconds, boosting accuracy and efficiency across times of peak demand.

Key techniques to implement now:

• Single source of truth: a common platform provides in-transit visibility and live stock levels, enabling same-day allocations and faster delivery decisions.
• In-transit tracking: real-time ETA feeds allow automatic rerouting to the closest fulfillment node, reducing slip times and improving customer promise reliability.
• Store-and-ship optimization: reserve online orders from both DCs and stores, then auto-allocate replenishment to where demand exists; this helps meet online and omnichannel delivery expectations.
• Cross-docking and wave picking: inbound goods are pushed directly to outbound orders, cutting handling times and increasing total throughput.
• Enterprise collaboration: vendor-managed inventory and supplier partnerships launched to align replenishment with forecasted demand; lowers stockouts and total landed costs.
• Analytics-driven replenishment: leverage trends, POS and online signals, and news signals to adjust orders and merchandise mix, ensuring future merchandise aligns with customer expectations.
• Delivery optimization: route optimization and multiple carrier options reduce lead times and improve delivery windows for online orders.
• Experience-driven operations: implement dashboards that show out-of-stocks by store and item, enabling proactive actions by store teams (and even Starbucks-like consistency in execution).

To measure impact, track accuracy, service levels, and productivity. Suggested targets: in-stock rate above 97%, fill rate above 95%, forecast accuracy within 10-15%, inventory turnover improvement of 8-15% year over year, and a 12-20% reduction in days of supply for fast-moving items.

These steps increase efficiency and create a resilient, multi-channel experience. By combining online, store, and delivery operations on multiple platforms, the retailer can maintain momentum as trends shift and customer preferences evolve, keeping merchandise where customers expect it and ensuring timely delivery across times and geographies. This will position the retailer for continued leadership in the future of omnichannel retail.

Real-time cross-channel inventory visibility across stores, distribution centers, and e-commerce

Adopt a unified, real-time inventory platform that streams stock levels across stores, distribution centers, and e-commerce via a single API layer, reducing errors and delivering comparable experiences for customers. This technology backbone clarifies what stock is where, enabling precise allocations instead of gut calls.

Create a single source of truth by integrating WMS, OMS, POS, and e-commerce feeds; enable ship-from-store with automatic allocation; equip stores with wearables to capture shelf data; connect DCs to replenishment cycles in seconds, before exceptions cascade into backorders.

Data from orders, returns, and transfers feeds forecasts, trends, and times of day adjustments; analyze what drives demand and how uncertainty will shift in peak periods. Translate raw data into actionable prompts that guide replenishment and allocation across stores and DCs. what you measure, you improve into clearer decisions that customers will notice.

Realistic outcomes include stock accuracy rises to 98–99% in stores and DCs, fill rates improving 10–20%, backorders dropping 20–35%, and overstock shrinking 5–12% at peak times. The gains come from faster feedback loops and tighter cross-channel coordination. Errors shrink as teams see the impact of each change in real time.

Implementation kicks off with a 90-day pilot in a subset of stores and DCs; define KPIs for order fill, accuracy, and times-to-ship; run a free webinar to train teams; launching a phased rollout with clear milestones and certifications to validate readiness. informa notes that early adopters gain faster time-to-value.

Examples show practical impact: ship-from-store reduces backorder pressure during busy periods; arctic-grade cold-chain controls protect temperature-sensitive SKUs; starbucks-style speed to shelf demonstrates how easy it is to keep the right product in stock, wherever it’s needed. This approach goes beyond theory and helps them act faster.

To sustain momentum, focus on what matters: data quality, governance, and ongoing optimization. What you measure, you improve–and the result is a repeatable, scalable model that will support demand shifts, supply volatility, and evolving shopper expectations.

Unified order management to coordinate online orders, in-store pickup, and curbside services

Adopt a centralized unified order management system (OMS) to coordinate online orders, in-store pickup, and curbside services, reducing wait times and boosting order accuracy. The system provides real-time visibility into inventory, delivery status, and returns, so every channel stays aligned and the customer experience remains smooth.

Retailers that launched an integrated OMS connect their POS, warehouse, and ecommerce platforms into a single workflow. This setup accelerates replenishment, minimizes stockouts, and guides packaging decisions for pickup and delivery, which strengthens brand consistency across their stores.

Trends show that every shopper expects flexible options; after they place orders, within this framework, offering online ordering with curbside pickup expands the shop’s reach and increases demand. The OMS retrieves status updates and informs staff when items are ready or retrieved for pickup, creating a seamless experience.

Key metrics track order accuracy, on-time delivery, and curbside wait times, plus comparable performance across stores. A focus on replenishment timing and returns handling helps the retailer balance demand across channels, enabling elevated customer experiences and stronger sales performance.

For assortments like snacks, the system harmonizes stock across stores and reorders from the most efficient nodes, improving delivery speed and reducing excess packaging waste. From online carts to curbside retrieval, the flow stays intact, with packaging optimized for quick pickup and reduced handling.

Introduced integration with loyalty programs and returns flow within the OMS empowers staff to retrieve items quickly and respond to customer requests. The approach continues to evolve as trends shift toward a unified shopping experience, making the retailer better positioned to boost their sales and maintain brand trust.

Location-level stock thresholds with automated alerts to prevent stockouts and overstocks

Recommendation: Set location-level stock thresholds at the item-store level and enable automated alerts that trigger when on-hand falls below the reorder point or rises above the maximum. Use a data-driven, velocity-based policy that is comparable across stores and aligned with omnichannel goals; this continues to support both curbside and online fulfillment and will reduce stockouts and overstocks.

Organize items into three velocity tiers and tailor thresholds to each tier and store size. Fast movers (speed > 15 units/week) should carry 2–4 weeks of demand as a buffer, mid movers (5–14 units/week) 1–3 weeks, and slow movers (<5 units/week) 0.5–2 weeks, with adjustments for seasonal spikes and lead times. For high-variance categories like wearables and furniture, apply a larger safety stock margin and a wider max stock window to absorb supplier variability.

Compute thresholds with practical formulas: reorder point ROP = lead time (in weeks) × weekly demand + safety stock; safety stock equals z × sigma(during lead time), where z corresponds to your target service level. For example, a product with weekly demand 60 units, a 1.5-week lead time, and a safety stock of 20 units yields ROP ≈ 110 units. Set a max stock around 180 units to cap overages. This approach protects content integrity and ensures continuity before peak periods, reducing elevated risk of stockouts.

Automate execution by linking the POS, warehouse management, and supplier portals. When a threshold breach occurs, automatically generate a replenishment order or a recommended order with vendor lead time, latest certifications, and a confidence score. Use alert channels that fit the workflow–mobile push for store managers, email for planners, and a dashboard for executives. This will shorten the cycle from detection to action and remove the thorn of manual reconciliation.

Navigating omnichannel demands transparency across channels. Align thresholds so in-store inventory supports online orders and same-store pick-ups without creating conflicting signals. For items named in the report as critical, like furniture and wearables, keep higher safety stock if content quality checks (certifications) or supplier reliability (e.g., Schreiner, nyse-listed peers) vary. A well-tuned system reports exceptions in real time and prevents overcommitment on popular items while preserving broad assortments across channels.

Implement a quarterly review cadence to adjust thresholds based on total sales, seasonality, and market news. Before each season, refresh velocity bands and update ROP/max to reflect new supplier SLAs and price protections. The outcome: faster response to demand shifts, reduced stockouts, and fewer overstocks, with a clear audit trail to inform future decisions and reports for leadership, including any updates that are reported to stakeholders and named in performance reviews.

Forecast-driven replenishment prioritization to optimize shelf availability

予測主導型の補充優先順位付けを採用し、予測シグナル強度、販売速度、およびサービスレベルへの影響によって最優先SKUを特定し、補充オーダーを正確に履行にプッシュします。 このアプローチは、補充を需要に合わせ、欠品を減らし、ピーク時の購買期間中の店頭在庫を改善します。.

Integrate a survey ショッパーの意図と店舗従業員のフィードバックを活用して優先順位を調整し、顧客と現場チームからのデータが補充計画に反映されるようにします。活用 テクノロジー 小売システムの信号を実行可能な注文に変換し、 取得済 より迅速な意思決定のための在庫データ.

リアルタイムな可視性を提供 in-transit 在庫も手元に確保し、 improved 補充速度と increased 当日配送のようなフルフィルメントオプション。コンテンツ豊富なダッシュボードは、 supply サービス目標の達成をサポートするためのデータ、予測アップデート、および店舗内の状況。.

ウェアラブル端末やモバイルデバイスを従業員に装備させ、棚の隙間を把握し、バックストックから商品を取り出し、補充サイクルを加速させます。これらのツールは、カテゴリーを越えた複数の優先事項への対応を支援し、バックルームの乱雑さを軽減しながら、顧客体験を向上させます。.

当日配送、クロスドッキング、自動補充ルールへの投資は、サプライヤーとの間のフィードバックループを緊密にし、輸送中の遅延を減らし、サプライチェーンの信頼性を向上させます。輸送中の可視性とサプライヤーとの連携により、サイクルタイムが短縮され、例外発生後迅速に対応できます。.

明確な指標とテストの設定： increased fill rate, improved 棚の在庫状況、購入後アンケートにおける顧客満足度スコアの向上などが挙げられます。これらの結果を用いて予測モデルとルールセットを調整し、コンテンツと背景が確実に店舗の現状と一致するようにします。.

With a continuous 改善マインドセットがあれば、これらの実践は役に立ちます。 最適化 購買者にとってより良い体験を提供すると同時に、より迅速なフルフィルメントも実現します。 increased 競合する小売業者間の効率性。.

チャネルおよびSKUパフォーマンス分析による在庫決定の改善

チャネル別速度とSKU優先度に基づき、4週間ローリング予測と高需要SKUの安全在庫を使用して、毎週の補充閾値を実装します。.

グローバル市場およびブランドライン全体における需要と履行パフォーマンスを比較する、統一された分析フレームワークを構築します。オンライン、店舗、モバイルチャネル全体で比較可能なSKUを追跡し、どのチャネルがより速いスピード、より高い充足率、より良い利益率を促進するかを特定します。コンテンツの品質が需要シグナルと顧客満足度に与える影響も考慮します。InformaダッシュボードとTechTarget Insightsからのデータは、モデルを検証し、オフィスを実際の状況に適合させます。.

需要、予測精度、充足率、エラー、フルフィルメント速度、および品切れといった、アクションにつながる指標に焦点を当てます。これらのポジティブな指標は、商品に関する意思決定を導き、価格設定やプロモーションに役立ち、在庫予測のエラーを減らします。このアプローチは、NYSE（ニューヨーク証券取引所）上場パートナーおよびブランド関係者をサポートし、社内全体で共有できる明確なデータドリブンのレポートを提供します。.

以下の表は、戦略をチャネルおよびSKUごとの具体的な行動に落とし込んだものであり、次サイクルで実行可能な目標値が設定されています。.