How Blockchain Can Solve Demand Forecasting Problems

Nov 20, 2019

This article was originally published on LinkedIn.

Creating a good demand forecasting system is a major challenge because it’s so hard to get trusted data. The difficulty is compounded by suboptimal sales forecasting — another symptom of siloed business data.

Good forecasting requires quality analytics, and that’s only possible with access to data from various sources, both internal and external. When every business in your supply chain handles data differently, the discrepancies lead to duplicative, often incorrect data that seriously impedes efficiency. That’s especially true for companies that have built up their ERP and CRM systems piecemeal over the years, using different systems for each.

With so many disparate systems, how can you ensure that the data you receive is trustworthy? There’s no way to know who validated it, nor a means of determining whether the data is consistent up and down the supply chain. Many manufacturers are turning to blockchain to close these gaps and ensure that all data can be trusted. Yet many still face barriers, as implementing an entirely new network across an organization and its supply chain can seem daunting.

Finding Value in Improved Data Quality

Most companies already have forecasting systems, and the data they collect can be highly valuable. However, that value differs when every company’s systems are internalized and separate from those of other companies in their supply chains.

The solution is to standardize how the supply chain as a whole collects, analyzes, and shares data. A blockchain network provides the trust and data privacy required to make that standard a reality for every company within the network. Data within a blockchain network is inherently trustworthy because no single entity has control of the data or business logic. The data is written within the blockchain and can’t be altered or tampered with once written in the network.

The significantly improved data quality leads to equally significant value when it comes to demand forecasting. Orders can be fulfilled on-time, every time, and manufacturers waste less material and product while still keeping customers happy. That’s because blockchain enables data safety and security, which affects demand forecasting in two important ways:

1. Creating trusted network-wide data

Blockchain’s most fundamental value is the ledger of data that it creates and makes accessible to every member within your supply chain network. It allows all parties to have control over what data they share through an encrypted chain and to manage who has access to that data both online and offline.

The data you share is shared across the entire network, where every permissioned member can view it on his or her own ledger. No single entity, or even group of entities, can change or alter the data without every other member knowing. This blankets all data in the network with a level of security and trust that was previously impossible to attain.

2. Keeping proprietary data separate and secure

Data regarding sales, inventory, manufacturing, and more are essential to the accuracy of your demand forecasting efforts, but many companies worry about risks of sharing more than they should. However, integrating blockchain technology doesn’t necessarily mean giving up control of all data or the legacy systems that house it.

Companies that collect high-value customer data may have the most valuable forecasting information but may also wish to leverage that data in new ways. Within a blockchain network, they can more securely share information on a permissioned basis without losing control over it and can even track the use of the data in order to effectively manage compensation for its use.

The key to solving your demand forecasting problems is to improve data integration from all parties within your supply chain. Blockchain provides the solution for companies to do so with optimal privacy and without losing any proprietary data. To learn more about how blockchain can improve your supply chain process, download our whitepaper

Post by Ramya Donekal

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