5 Ways Data and Analytics is Changing the Supply Chain Landscape

Posted by Philip Driver on Apr 1, 2019 8:57:40 PM
Philip Driver

Your supply chain is generating big data. Knowing how to turn it into insights can transform your organisation.

The amount of data being generated every day by businesses of all sizes can be measured in the quintillions, with nearly all the data currently stored having been created in just the last year. This digital shift is impacting many areas of business and supply chain is no different.

Many companies now cite managing, analysing and - most importantly - getting insight from big data as their number one challenge. The speed of change is unprecedented. Many supply chain and logistic focussed companies are struggling to keep up, let alone implement the solutions and processes that will harness this valuable resource. Get it right and the competitive advantages are obvious.

Supply chain management is typically geared towards efficiency and cost saving. With the advent of IoT and more data driven approaches, companies that can invest in analytics and data will potentially save millions of dollars in improvements to efficiency and velocity.

In fact, many companies are moving towards digitized real time supply chain models, where real time interventions at factory level become possible. Data can now be harnessed at scale to drive marginal gains that can add up to large cost savings.

Data and Analytics for Supply Chain

Where does data fit in the supply chain?

The key areas where data can help across the entire supply chain landscape are:

  • Supply Chain

Almost the entire process can benefit by harnessing data to provide insight that drives efficiency across sourcing, manufacturing, distribution, warehousing and fulfillment.

  • Marketing

We are moving into an age of real time feedback. This is most evident where businesses need to be increasingly customer focused. Customer data is being used to power supply chain decisions from pricing to affinity analysis and forecasting.

  • Logistics

For a long time logistics companies have had a laser-like focus on using data to drive efficiency. For example, for over 20 years now UPS has used tracking data to monitor impactful events like extremes of weather to build optimised route plans. They are the experts at using location-based RFID technology to provide real-time tracking to end users.

  • Operations

Another area historically driven by cost efficiencies is Operations, be it inventory management or labour utilization. To achieve any improvements in efficiency, businesses must now monitor performance and react in almost real time - impossible without high levels of insight-enabling data.

  • Sourcing

Sourcing for many companies represents their single biggest category spend and the associated risk around this can make or break a business. Using data to improve sourcing decisioning can drive huge cost savings.

The right data for logistics and supply chain


Supply Chain Data & Analytics: Who’s doing it right?

A great example of an organisation using data and insight to create an agile and efficient supply chain machine is the high street fashion retailer Zara. Zara has built the kind of best-in-class infrastructure, processes and a data driven approach that leaves their competitors in the dust. They continuously collate and analyse consumer demand constantly across 93 markets, with their concept-to-store turnaround being just 21 days.

Unfortunately, the gap between the leaders in these areas and most normal businesses is increasing. Many companies lack the internal capabilities, knowledge and training required to gain that all-important competitive advantage.

Many businesses are either still relying on old school-style spreadsheet-based planning or are simply overwhelmed by the sheer volume of data to be able to organise it to gain any relevant and commercially interesting insight.

Tracking problems persist, and knowledge gaps cause inefficiency, with the resulting rigid processes that then restrict business agility.

The Challenges

The main issues companies face when thinking about data for supply chain are:

  • Data Paralysis

As mentioned, the amount of data available to work with is increasing constantly. The task is in organising , understanding and creating insight from it. It’s very easy to get lost in the data or simply spend far too long looking at irrelevant information. Data may also have a “use by date” in that companies can spend too long or impose too rigidly accurate expectations on insight. Before they know it the chance to act is gone.

  • The Wrong Kind or Too Many KPI’s

Just being able to measure something doesn’t necessarily mean you should! Many companies attempt to track hundreds of performance indicators, many of which are either not tied to business objectives or simply vanity metrics with no practical application. Taking time to align your KPIs to strategic company objectives will save you time and resources further down the line.

  • Lack of a Defined Strategy

In their haste to become data driven we see many companies rushing out to sign up teams or data analysts or purchasing enterprise level data platforms without any clear strategy in place. Invariably costs mount up and results are random at best. Many businesses end up “busy being busy”, attempting to find insight through sheer force of will. In many cases they arrive at poor decisions because they’ve misinterpreted correlation as causation.

Getting Started

However for most supply chain focussed companies the main barrier to becoming data enabled is simply not knowing where to start.

At CommerceCentric whenever we undertake a new data and analytics project, we always follow four simple steps.

  • 1. GOALS: Defining your business objectives and associated KPIs

This is essential to understand both what you are trying to achieve as an organisation and if you’re measuring yourself correctly.

  • 2. STRATEGY: Defining a Data Strategy

We map your digital maturity from where you are now to where you want to get to. We define your data team, tools and processes. We link the data strategy to your company objectives and create clear and measurable goals with trackable and valid KPI’s.

  • 3. ADDRESSABLE DATA: Finding your data

We identify and catalogue the data you can address or want to address, where possible aligning all your data sources. We retrieve, merge and begin to analyse in line with strategy and capabilities.

  • 4. INSIGHTS: Creating business useable insight

And not insight for insight’s sake. We start small and increase the complexity over time. We democratise your data through visualisation and company training. Data is not just for analysts!

Data and Analytics in Logstics and Supply Chain 

To learn how CommerceCentric can help you get to grips with data and analytics, contact us for a free assessment.

Topics: Data Analysis, Big Data, Logistics, Supply Chain

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