Understanding Analytics for Supply Chain: Demand, Inventory and Performance Management

By Vuealta
4 min
Published: 13 May 2021

Understanding Supply Chain Analytics Defines Your Position On The Value Chain

Anaplan is to planning what Salesforce is to CRM and what Workday is to Human Resources (HR), but planning as a pure-play practice is a multifarious discipline in and of itself.

We can think of business planning at the highest level as a broad brush term covering everything from financial tracking and recording mechanisms to business operations orchestration and everything in between. But one of the most dynamic elements of modern business planning is supply chain planning.

The importance of supply chain analytics, can not be overstated. If you (as a company) understand how supply chain analytics work, then you (and your business) can understand where to place yourself on the entire value chain of the commercial model  and market that your business operates in.

Supply chain digitization

The interest in supply chain analytics as a whole was fueled massively by the advent of the Internet, which of course gave us the ability to connect and examine our world in a far more granular way. The next major watershed moment came with the development of cloud computing and all the infrastructure, platforms and services within it.

Cloud data storage today means we can store more data than ever previously imaginable. This reality helped drive the initial adoption and development of digital supply technologies. Today, some two decades after the millennium, we can also now gain access to much cheaper cloud-based ‘compute’ to be able to drive our supply chains with digital analytics technology. 

Combine these facts with the fact that today’s compute power also enables us to deliver an increasing amount of Artificial Intelligence (AI) and Machine Learning (ML)-based advancement… and you start to get an idea of how powerful these tools can be.

When the sales team can get forecast-value-add, they can operate more effectively, efficiently and ultimately, more profitably. This holds true for most businesses, apart from those in extremely bespoke custom-commodity markets, where the order book effectively represents the supply chain plan.

Steering a business with a digital supply chain 

Embracing the use of digital supply chain technology enables a business to anticipate the future, rather than extrapolating the past. That same business is then able to flexibly leverage internal and external drivers to steer internal actions in accordance with the shape of the digital supply chain that it operates in.

A progressive organization adopting this approach to digital operational strategy can then deliver agile planning with frequent dynamic re-assessment. The firm gains predictive insights from AI/ML for augmented sales and marketing insight

The end result, for customers, are better experiences, interactions and touchpoints with the business; this is a direct result of the business has observed a reduction in forecasting errors using Artificial Intelligence. Looking forward, the digital supply chain then becomes the greatest single area, zone, commodity or entity for innovation to be applied in relation to any company’s investments in digitization analytics and automation.

If there is a key challenge here for organizations growing to embrace the use of digital supply chain technology, it is formulating and running an operational structure where it is possible to consume those insights effectively. Too often, where the presence of supply chain analytics insight does exist, it happens in silos across the business, so this is clearly not a cohesive and productive approach.

Bridging the insight gap

We know that the reality inside many businesses is that you have individuals on the ground, all operating within different planning systems. But where those individuals are is also the point where they need to take action and make the decisions to actually affect what’s going on in the supply chain. Bridging the gap between the analytical insights and the ability to put those into action remains the primary challenge.

Decomposing trends versus seasonality to find base levels of market volume enables organizations to understand where spikes exist and where averages prevail. Being smart enough to know the difference between variability and uncertainly is the smart operator’s sweet spot. 

As we have stated in our title here, the action of understanding supply chain analytics enables an organization to define, direct and deliver upon its position on the total value chain that drives the business lifecycle in any given marketplace. As business lifecycles themselves become digital entities, organizations that use supply chain analytics to track their place on that lifecycle will form the strongest links on the value chains of tomorrow.

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