Solvoyo i Enavate ogłaszają strategiczne partnerstwo mające na celu przyspieszenie wdrożeń rozwiązań ERP i prognozowania AI

Adopt a unified ERP and AI forecasting strategy now to boost zwinność within your operations and to deliver faster, data-driven decision-making.

Solvoyo and Enavate announce a strategic partnership that aligns ERP execution with AI forecasting across platforms and cloud-based tools, enabling 24×7 availability, flexibility, i a user-friendly experience that keeps data and insights available when teams need them.

Within the first 90 days, the joint solution will streamline ERP configuration and forecasting for clients in diverse industries, including retail, manufacturing, and distribution, while ensuring the platforms remain intuitive and that data pipelines are available to teams around the clock and across time zones.

khandelwal, a leader at Solvoyo, notes that the alliance gives credit to frontline teams by empowering them with real-time insights and simple workflows, boosting decision-making across finance and operations. These capabilities will help organizations respond to emerging demand and supply constraints while maintaining zadowolenie with ERP and forecasting outcomes.

Define joint value, industry focus, and implementation approach

Adopt a joint value proposition by integrating Solvoyo’s predictive forecasting with Enavate’s ERP to reduce forecast errors, optimize purchasing, and accelerate value realization for small-business manufacturers and distributors. Target outcomes include a 15–25% uplift in forecast accuracy, 10–20% fewer stockouts, and a 10–15% improvement in working capital cycles within the first year. The solution is modular and fits into existing windows of planning cycles, enabling rapid deployment without disrupting current operations. Most impact occurs in manufacturing and high-variance distribution contexts where accurate demand signals directly narrow cash-to-cash cycle times. This collaboration can play a decisive role in shortening time-to-value for small-businesses that rely on planning accuracy.

Industry focus primarily targets manufacturing, wholesale distribution, and light assembly, with emphasis on small-business segments that manage multi-SKU portfolios. The joint offering uses predictive signals to adjust reorder points and safety stock and treats demand sensing, inventory optimization, and purchasing planning as a unified workflow. The platform uses cross-functional collaboration and dynamic planning to reduce cycle times. technavios reports indicate AI-driven forecasting within mid-market ERP ecosystems is expanding, aligning our collaboration with market demand and enhancing investors’ confidence. This approach targets critical points in the supply chain.

Implementation approach follows a four-stage plan: 1) discovery and data readiness, mapping ERP, WMS, and manufacturing data while establishing governance; 2) integration and model alignment, including API connections and SKU mapping; 3) pilot on a representative manufacturing line using ipad for shop-floor views and windows-based dashboards for planners; 4) scale with a documented rollout, change-management playbook, and a customisable set of dashboards and reports. This plan has been validated in pilot deployments and been refined with feedback from manufacturing teams. The rollout includes training and a detailed document that outlines governance, roles, responsibilities, and risk controls.

Governance, metrics, and next steps center on a joint steering group with representatives from Solvoyo and Enavate; define KPI thresholds (forecast accuracy, service level, inventory turns, days of inventory) and a single source of truth. The collaboration emphasizes a shared document repository for decisions, risks, and changes, and uses cloud-based infrastructure to support remote teams within a secure environment. The expected impact includes revolutionizing planning processes, improving purchasing and production alignment, and delivering measurable gains for small-business customers. This approach also strengthens investors’ perspective by demonstrating a scalable, repeatable model that delivers clear ROI.

ERP modernization roadmap enabled by Solvoyo and Enavate integration

Adopt a phased integration plan that unifies Solvoyo forecasting with Enavate ERP to unlock streamlined operations, gain measurable results, and establish a monthly cadence for billing and reportinganalytics across the entire organization.

This collaboration hinges on a clear partnership between Solvoyo and Enavate, a cross-functional team, and governance that aligns IT, finance, and operations. Currently available APIs and pre-built connectors enable faster start, reducing time-to-value and enabling the entire network to find better ways to operate.

The roadmap begins with a midsize-business pilot to test demand forecasting, inventory optimization, and digital billing alignment, with a focus on smoother billing cycles and faster reportinganalytics delivery. After proven success, extend to small sites and scale toward industry-specific configurations.

Key enablers include a unified data model, a streamlined network of data flows, and a set of ready-to-use solutions that deliver improved reportinganalytics dashboards and actionable insights. The integration supports extra data quality checks and better optimization of stock and capacity, driven by a customer-centric approach.

Measure success with monthly dashboards showing forecast accuracy, inventory turns, billing cycle time, and cost-to-serve. ROI depends on adoption speed, data cleanliness, and the depth of the digital integration; plan to realize gain in the first quarter and expand to the entire network by the next fiscal year.

In a manhattan hub, the combined platform reduces bottlenecks in reportinganalytics and strengthens collaboration across the industry. Partners find that the new path supports end-to-end operations, from planning to invoicing, with a single source of truth that is available to finance teams and field ops alike, boosting trust in the partnership and accelerating optimization.

AI forecasting capabilities tailored to demand planning and inventory optimization

Adopt ai-powered forecasting across the Solvoyo-Enavate platform to synchronize monthly demand planning with inventory optimization across distribution networks. Build a unified data fabric blending historical sales, promotions, seasonality, and supplier lead times to produce precise forecasts that drive purchase quantities, safety stock, and distribution allocations for small-business and wholesale segments, providing actionable insights for replenishment.

The research models use multiple signals–sales velocity, promotions, market events, and lead-time variability–to adapt to changing dynamics. This approach provides an overview of expected demand and inventory requirements, while reducing stockouts and excess stock by making planning decisions more data-driven across multiple warehouses. It focuses on optimizing service levels and inventory turns. The team collaborates to develop new models to capture micro-trends. Active research informs every forecast.

Enavate’s service layer ensures data quality and governance, enabling monthly scenario planning–base, optimistic, and conservative–and benchmarking forecast accuracy. The workflow includes ensuring data quality at every step. Integrations with e2open and coolgix keep supplier capacity and payment terms aligned, while dashboards on ipad give planners real-time reviews and quick actions.

Focus on measurable outcomes: forecast accuracy (MAPE, sMAPE), bias, service levels, fill rate, inventory turnover, and stockouts. Provide an overview of forecast performance to leadership and teams, with khandelwal providing interpretation and recommended improvements. This close loop between forecasting, planning, and purchasing, and it supports better payment cycles and cash-flow management.

For small-business models and broader distribution, the ai-powered forecast scales with the platform, enabling ongoing research, development, and refinements through the Solvoyo and Enavate alliance. Small teams benefit from streamlined workflows, monthly dashboards, and seamless integration with e2open and coolgix, all focused on quality service. Reviews from customers and field teams provide concrete input for ongoing improvement.

Data integration and governance for unified ERP analytics

Implement a centralized data fabric with clear lineage and automated validation to unify ERP analytics across departments. Appoint a chief data officer to drive governance, with data owners in finance, operations, procurement, inventory, and sales. Create a single source of truth by aligning master data including customers, suppliers, products, locations, and vendors. Define data models, naming conventions, and metadata tagging; implement an open-source data catalog or a vendor solution. Enable ai-powered data quality monitoring to detect anomalies and fix issues before they reach planning and reporting. Set access controls and encryption; ensure data is shared through APIs and secure pipelines, ensuring policy compliance across borders. Build a phased rollout with georgia office pilots and international teams before scaling to wholesalers and distributors. Develop a training program to upskill staff on data stewardship, quality checks, and standard reports. Use a demo dataset to validate use cases and measure optimization, including planning, forecasting, and inventory across departments.

Frame a pragmatic governance play that answers key questions: who identifies data issues, who approves changes, and how we measure impact across departments. Schedule quarterly reviews with the chief data officer and cross-functional leaders to adjust roles and policies. Lean on research-backed best practices to shape data contracts, data quality rules, and cross-border sharing. Plan for cross-system data feeds, versioning, and change management; specify data owners and escalation paths. Include both open-source and ai-powered components where possible to accelerate delivery while maintaining control. The governance playbook outlines roles, approvals, and data controls, and a quarterly demo shows progress to wholesalers, international teams, and other departments. Monitor metrics such as data availability, refresh latency, and user adoption across departments. georgia teams’ feedback loops ensure policies stay aligned with real-world needs.

Industry-specific use cases: manufacturing, retail, healthcare, and logistics

Start with a 90-day pilot in Massachusetts to validate cross-industry forecasting benefits, showing gains that attract investors and reassure customers. Integrate Solvoyo’s AI forecasting with Enavate’s ERP, and use a single reporting analytics dashboard to track entire value chains, including inputs from supplymint data feeds and open-source modules where appropriate.

• Produkcja

  • Improve forecast accuracy by 18–25% across key SKUs, reducing stockouts and excess inventory during peak periods. Use through API connections to pull data from supplier schedules and internal production planning to align capacity with demand signals.
  • Optimize master production schedules by simulating scenarios (capacity, supplier risk, and lead times) and sharing executive dashboards for quick decisions. Report that inventory turns rise and working capital needs tighten over the period.
  • Standardize data inputs from ERP and open-source analytics to deliver easy, repeatable forecasting workflows. Provide training videos for shop-floor teams to accelerate adoption and security controls to protect sensitive data.

• Sprzedaż detaliczna

  • Use forecasting to optimize assortments and promotions across channels, increasing margin opportunities while maintaining service levels. Link to Coupa for purchase planning to consolidate spend and reduce lead times.
  • Forecast demand at the store and regional level, then cascade to replenishment orders through the entire supply chain. Estimated improvements in stock coverage and on-shelf availability drive better customer experiences.
  • Leverage reporting analytics to monitor campaign lift, markdown effects, and seasonal demand shifts; publish executive-ready metrics to investors and partners.

• Opieka zdrowotna

  • Forecast consumables and equipment demand to minimize shortages during period spikes, using historical usage data and real-time alerts. Ensure security and access controls for patient-facing inventory data while sustaining easy access for operations teams.
  • Coordinate with suppliers to align procurement with clinical demand, reducing waste and carrying costs. Use massachusetts-based facilities as pilots to demonstrate measurable improvements in service continuity.
  • Provide clinicians and administrators with open dashboards that combine utilization, cost, and outcome metrics, supported by reportinganalytics to inform procurement decisions and policy discussions with investors.

• Logistyka

  • Enhance warehouse throughput and last-mile reliability by forecasting arrival windows, dock readiness, and carrier capacity. Use throughputs and cycle times to optimize staffing and equipment utilization.
  • Planuj zmiany sieci za pomocą prognozowania scenariuszowego, które uwzględnia zmienność popytu, koszty paliwa i ograniczenia przewoźników. Mierz zyskowność okres po okresie w zakresie terminowości dostaw i zmniejszenia kosztów wysyłek ekspresowych.
  • Publikuj pulpity nawigacyjne operacyjne, które podkreślają wyjątki, alerty bezpieczeństwa i wskaźniki kosztu obsługi; zapewnij dostęp dla kadry kierowniczej i menedżerów operacyjnych w celu szybkiego podejmowania decyzji.

Plan wdrożenia kładzie nacisk na ponadfunkcyjne zarządzanie, otwarty dostęp do danych dla zespołów oraz regularne przeglądy kierownicze. Dopasuj projekty pilotażowe do publicznie raportowanych możliwości z badań Technavio i wskaźników branżowych, aby ustalić realistyczne cele i ramy czasowe, jednocześnie monitorując oczekiwania inwestorów dotyczące skalowalnych rozwiązań ERP i prognozowania.

Harmonogram wdrożenia, kamienie milowe i prognozy zwrotu z inwestycji dla klienta

Rozpocznij od 12-tygodniowego projektu pilotażowego w międzynarodowych węzłach dystrybucyjnych i wśród pracowników, aby zweryfikować dokładność prognoz i zwrot z inwestycji przed wdrożeniem na pełną skalę.

Wdrożenie będzie realizowane zgodnie z planem podzielonym na etapy, który skupi się najpierw na instalacji i integracji, a następnie na testach praktycznych z wykorzystaniem rzeczywistych danych dotyczących popytu. To podejście buduje zaufanie wśród liderów biznesu i pomaga pracownikom znaleźć odpowiednią równowagę między automatyzacją a osądem eksperckim. Rozwiewamy obawy na wczesnym etapie, wyznaczamy jasne oczekiwania i zapewniamy regularne aktualizacje poprzez komunikaty e-mail oraz dedykowaną stronę projektu, aby utrzymać wszystkich interesariuszy w zgodzie.

Podczas wdrażania system zostanie skonfigurowany pod kątem rozszerzonej funkcjonalności prognozowania, która napędza podejmowanie decyzji ukierunkowanych na wzrost. Wdrożenie wykorzystuje przyjazny dla użytkownika interfejs tabletowy dla pracowników magazynowych oraz pulpity nawigacyjne na komputerach stacjonarnych dla planistów, z monitorowaniem 24×7 w celu wykrywania anomalii i uruchamiania proaktywnych działań. Międzynarodowy zakres zapewnia, że zespoły zaopatrzeniowe, dystrybucyjne i instalacyjne mogą współpracować w czasie rzeczywistym, wspierane przez najlepsze praktyki i pojedyncze źródło prawdy we wszystkich rynkach.

Kluczowe kamienie milowe i wyniki podkreślają praktyczne korzyści: zwiększoną widoczność zapasów, szybsze cykle decyzyjne oraz usprawnioną współpracę pomiędzy pracownikami w różnych działach. Aby utrzymać dynamikę, dbamy o prostą instalację i skupiamy się początkowo na modułach o największym wpływie, a następnie rozszerzamy zakres, gdy wyniki potwierdzą wartość partnerstwa.

Projekcje ROI opierają się na zdyscyplinowanym podejściu opartym na danych. Oczekujemy, że ulepszone prognozowanie zmniejszy brak towarów i przestarzałe zapasy, poprawi poziom obsługi i obniży nakład pracy ręcznej w zespołach dystrybucyjnych, produkcyjnych i sprzedażowych. Poniższe scenariusze dają praktyczny pogląd dla decydentów, gdy podejmują kolejne kroki. Założenia obejmują pilotaż w 3 regionach, 6 lokalizacjach z umiarkowaną bazą liczby SKU i standardowy koszt utrzymania zapasów 20%. Wzrost sygnałów popytu będzie wspierany przez prognozę opartą na sztucznej inteligencji, a urządzenia tablet umożliwią pracownikom terenowym reagowanie na wiedzę w czasie rzeczywistym.

Założenia leżące u podstaw modelu ROI obejmują układ dystrybucji w 3 regionach, 6 lokalizacji oraz 100 000 SKU o zmiennej sezonowej podaży. Dokładność prognozowania poprawia się o 15–25%, braki w zapasach maleją o 30–40%, a koszty utrzymania zapasów maleją wraz z dostosowaniem zapasów do rzeczywistego popytu. Framework uwzględnia również monitorowanie 24×7, proaktywne powiadomienia e-mail oraz usprawniony proces instalacji, który minimalizuje zakłócenia w działalności podczas wdrożenia. W rezultacie otrzymujemy praktyczną ścieżkę do mierzalnej poprawy w kluczowych wskaźnikach biznesowych, z wyraźnym punktem decyzyjnym dotyczącym skalowania w oparciu o zaobserwowane zyski i opinie od międzynarodowych współpracowników. Strona z aktualizacjami projektu informuje wszystkich, a paliwem dla dalszego wzrostu są ciągłe ulepszenia w zakresie planowania zaopatrzenia, efektywności dystrybucji oraz przyjaznych dla użytkownika interfejsów, które umożliwiają zespołom szybkie i dokładne podejmowanie decyzji.