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Importance of Near Real-Time Data for Better Demand Planning and Visibility

April 18, 2022

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Companies serving local and international markets often face challenges while working with a complex network of global demand-supply chains. Their challenges vary from inventory management inefficiencies to delayed responses to market indications.

Poor demand planning can be cited as one of the key reasons here. And demand planning relies heavily on data. Let’s explore the complex relationship in depth.

Importance of Data for End-to-end Supply Chain Visibility

Supply chain demand planning is crucial to help predict the demand for products in near real-time to ensure they are delivered when the customers need them.

Hence, the demand planning process balances supply/inventory and market demand for products and services. Sadly, the entire process will remain unrealized in the absence of data, giving birth to other subsidiary challenges.

Let’s take a look at how a global sports merchandiser increased their demand visibility by 60% with near real-time data harmonized from myriad sources.

The client, a global multibillion-dollar corporation, conducted its sales through a network of multiple intermediaries such as wholesalers, distributors, single-brand and multi-brand retail outlets. They were thus looking for a partner to enable their POS data acquisition. They faced many process and business challenges elucidated below:

Process Challenges

The difficulty of data collection: Too many human touchpoints in recording and data extraction for demand planning complicated the entire process and increased errors.

Non-standardized data capture: Each retailer / distributor / partner followed their own point-of-sale (POS) system. This obstructed the seamless flow of data to the parent organization. Most data captured was deemed asynchronous and useless.

Delays in data flow: Onboarding a partner often took 12-18 months. Further, data remained unavailable for weeks.

Business Challenges

Inefficiencies in inventory management: Since accurate and timely data was not available, sales and supply chain leaders failed to optimally manage the existing inventory of finished goods across markets.

Inability to perform demand planning: Without data, clear real-time visibility into sales performance across regions, products, and other dimensions was unachievable. Hence, planners worked on demand planning using sell-in data (no. of products sold to retailers) instead of the more precise sell-through data (no. of products sold to customers).

Low trust in data: Most data received from different elements in the demand-supply chain network was not streamlined and consolidated. Hence, analytics derived from such data during demand planning were considered untrustworthy or unreliable.

Sub-optimal response to market dynamics: Slow onboarding of partners (which took 12-18 months), delays in data availability (as much as weeks), and poor data quality meant that companies failed to respond to market indications appropriately or on time.

How can Global Data Acquisition and Harmonization Help in Better Demand Planning & Visibility?

Demand planning software solutions like TradeEdge can easily foresee global data acquisition and harmonization for better demand planning.

The systematic, process-oriented approach of TradeEdge is easily adaptable to the client’s ecosystem while working closely with the leadership team, studying their data acquisition process; interacting with multiple stakeholders like client vendors, client partners, business team, technical teams, and market leads; and involved in various stages of the product lifecycle.

Benefits of Data Acquisition and Harmonization:

With access to real-time harmonized data, the global sports merchandiser enabled end-to-end supply chain visibility across the ecosystem. Below are a few benefits:

The New Way Forward

Demand planning has become an integral part of businesses following massive disruptions and challenges during the pandemic. That was a wake-up call for all and highlighted the importance of global data acquisition and harmonization for better demand planning and visibility across the value chain.

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