Supply Chain Planning in the Digital Business Era

By Akhil Oltikar, Co-Founder and CEO, Omnics, Inc.

We live in a world of unprecedented data generation, business speed and innovation. Spreadsheet planning is unsustainable in this digital business era. To keep up, a new set of solutions is needed that automate non-value add tasks, unify data across the supply chain and provide smart answers.

We live in a world of unprecedented data, speed of business and innovation. Over 90% of today’s data in the world has been created in last two years. Total data will grow 50X from 2010 to 2020¹. This applies to supply chains too as they are no longer vertically integrated organizations but an ecosystem of manufacturing partners, suppliers, logistics services providers and retailers. Product life cycles are shortening and speed of business is faster than ever. It took 75 years for a telephone to reach 50 million users. Television took 14 years to get there and iPod took 3 years (…while Pokemon got there in 19 days!). Innovation at all levels including product, technology and business model is giving rise to newer business that are challenging the incumbents. In 1920s, the average lifespan of a company on S&P 500 was 67 years. That dropped to 25 years in 1980s and 15 years in 2010s. In 2020s, 75% of the companies will be the ones NOT on the index today².

Every product around you has a supply chain. Companies along the supply chains of these products need to deliver their products at lowest cost, highest quality and fastest time while achieving profitable growth. Supply Chains have become a competitive advantage and companies are doubling down on this by digitizing their operations. Every action and reaction in supply chain operations generates data. As companies digitize this data it is imperative to implement tools to extract, analyze and collaborate this data to realize the full potential of a digital supply chain.

 

So how do you go about advancing your supply chain planning function in this digital business era?

1. Automation: We all perform certain repetitive tasks at work. Bi-Weekly or monthly planning cycles have a significant amount of tasks that are repetitive and non-value add. For example, downloading data from transactional systems, copy-paste parts of that data into the master planning spreadsheet model, running pivots, creating charts in spreadsheet to analyze results, uploading the results back to ERP to execute. Map your planning process to identify the value-add vs. non-value-add activities. Automate the non-value add activities and make your planning team efficient. Let the machine perform those tasks while the team focuses on the outputs, running what-if scenarios and analyzing potential opportunities to improve business performance.

 

2. Unified Data Model: Planning starts with data. The planning logic could be unique or may become unique as business conditions change, however the input data is always more or less the same in supply chain planning. A planning solution requires a unified data model, which is a single version of truth in terms of data format, and its interpretation across the organization, assuring data integrity and lineage as it is being used across different functional groups and by different tools. Using a unified data model not only collects the data and reports it but also helps connect the dots between data sets and categories.

 

3. Optimization and Machine Learning: It is important to have efficient and effective planning with the resources on hand but extremely important to leverage the historical planning data to make subsequent planning cycles smarter. Planning data holds a wealth of information about your supply chain operations, actions and results. The data size gets big very quickly and, simply put, a human brain cannot analyze this big data with basic tools. In more than 90% of cases, this data is discarded or lost due to constraints of spreadsheet planning.  Augment human intelligence with cutting-edge technology. There are multiple steps towards advanced planning. It starts with the application of basic optimization algorithms to identify areas of improvements like inventory, capacity, distribution and trade-offs between them. Though the benefits of optimization are well known, it is used proactively. Machine Learning (ML) is used in predictive solutions. ML application in analyzing historical patterns, inputs and resulting outcomes help you in key areas like forecasting demand/supply, inventory shortages and automatically generating a PO with suppliers, dynamic replenishment at component level has become a reality.

 

Digitization is driving exponential increase in data size and global supply chains need faster and smarter answers. Supply chain planning with spreadsheets is simply unsustainable. Augmenting human intelligence with smart tools for supply chain planning gives you a competitive advantage in today’s digital supply chain era.

Omnics provides supply chain planning software solutions that help companies make sound, data-driven, timely decisions while transforming data into a competitive asset. Omnics software platform’s suite of capabilities includes extracting, processing, analyzing and collaborating your supply chain planning data.

Sources/References:

1. IDC Research
2. Richard Foster – Yale University