The rise of IoT in supply chain planning

July 10, 2017

 

 

There’s no denying the Internet of Things (IoT) has taken hold of nearly every aspect of our lives. With the number of connected devices estimated to surpass six billion next year and more than 20 billion by 2020, the steady stream of data these devices are providing can easily crowd and clog your supply chain planning processes if you’re not prepared.

 

When it comes to your supply chain planning, the data sourced from IoT-enabled devices lets you continuously sense, communicate, analyze and act

Examples of this already exist in the marketspace. Coca Cola’s Freestyle machines, which enable end consumers to select their own unique beverage flavor combination has already inspired the creation of new mainstream and traditionally distributed products. Take the launch of Cherry Sprite. The data coming from the Freestyle machines let Coca Cola see which flavor combinations were most often selected by people across locations and determine if there was any seasonality to it. What they found was a demand for cherry flavoring added to traditional Sprite.

 

HP’s Instant Ink has transformed a section of the printer manufacturer’s business model into a subscription-based revenue model, and transformed part of its supply chain in the process. HP’s new venture uses smart printers that sense each drop of ink being delivered to a page so it can monitor ink levels and order and ship new ink cartridges before you run out. That means better forecast accuracy for HP, but also a change in how and where to handle distribution and logistics.

 

These examples relate to the second of Downard’s macro trends—digital business.

 

Digital business is about ideas and models that blend the digital and physical worlds. It creates a convergence of people, business and things. While the above real-world examples of how IoT is affecting supply chain planning were mostly related to retail or business-to-consumer (B2C), there are business-to-business (B2B) examples of digital business, as well.

 

That means before you jump into this new reality, make sure your supply chain planning is ready to handle IoT button orders. Downard suggests the following:

  • Choose low variability, high volume products with well-defined fulfillment pathways

  • Prepare for direct and indirect demand drivers across multiple channels

  • Use participation in IoT button programs to deepen the retailer relationship in other areas

With the advancement of IoT and digital business comes Downard’s final macro trend—algorithmic planning.

 

Algorithmic business, powered by algorithmic planning, represents a future where supply chains can act and negotiate on their own. It’s the evolution of decision support levels, culminating in non-optional automation where smart machines and AI make the decisions and we abide by them.

Here are the levels of decision support as outlined by Downard:

  • General information—give me the facts (use historical data)

  • Specific information—give me a suggestion (statistical forecasting)

  • Advisory guidance—help me as I go (automated alerts)

  • Opt-in automation—Do this complex task for me (run multiple forecasting models and recommend the best fit)

  • Automation that can be over-ridden—take responsibility for this task until I tell you otherwise (automatic re-order points for replenishment)

  • Non-optional automation—take responsibility for this task and don’t let me or anyone else interfere

 

These macro trends—IoT, digital business and algorithmic planning—are causing a shift in supply chain, more emphasis is being placed on algorithmic skills. That means delegating manual and simpler tasks to robots or machines, and investing in talent with a better blend of supply chain, IT and analytical skills.

 

Downard ended his presentation with some recommendations to get you ready for IoT in supply chain planning. They are to:

  • Understand the fundamental changes required for digital maturity in supply chain planning

  • Ensure supply chain planning is a strong, recognized player in your company’s decision to build digital business partnerships

  • Identify data that you can leverage in supply chain planning algorithms

  • Balance the skill set of your team to match what’s needed for digital business and algorithmic planning

 

 

 

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