Why You Should Look Into the AI Black Box
As retailers invest in their commerce transformations and put their trust in the power of artificial intelligence (AI), they need to ensure their whole organization is aligned to make the best use of it. Historically, the decisions and logic of AI has been somewhat of a mystery to the stakeholders and those who are putting trust in AI. When the “black box” is turned into glass box, an organization gains confidence and clarity. The glass box I am referring to is a view into the workings of the technology; transparency into the inputs, data and factors orchestrating the autonomous decisions. The glass box concept provides a view into the black box that most people feel around AI; it provides evidence and confidence of everything happening inside – both technical algorithms and human activities – are fit for purpose. In effect, it refers to clarity and insight across the process of orchestrating supply chain automation and AI-led transformation.
As retailers continue to support omni-channel commerce and manifest customer-centric supply chains, there are several areas of cross-functional collaboration where they are seeking the value of AI. We see four major areas to address:
- Real-time inventory: The placement and extent of stock anticipated in stores, warehouses and local fulfilment centers to meet store, online and BOPIS (buy online pick in-store) orders.
- Fulfilment transparency: The ATP (available to promise) methodology that ensures a retailer isn’t breaking promises around availability or timing of deliveries.
- End-to-end order visibility: A holistic overview of the entire supply network (including labor, business partners, capacity, maintenance, etc.).
- System scalability: The evolution as demand ebbs and flows relative to current capability.
Organizations are looking to get a grip on these areas by using AI and machine learning (ML) to replace cumbersome manual processes and to better predict what is needed, when and where. While there seems to be lingering doubt in the minds of the stakeholders, that doubt pertains to the benefits they will yield and not necessarily the need or value of automated intervention. This is often exacerbated by the sheer number of digital transformation initiatives to create a more connected and intuitive supply chain.
They know the data needed, the desired outcomes, and even who will use them. But stakeholders are sometimes blind to why the decisions are being made and are seeking assurance that outputs are orchestrated efficiently and effectively. This is why businesses need to turn their black box into a glass box.
Transparency, Visibility and Clarity From the Glass Box
The glass box provides clarity to tangibly connect the data inputs and desired outcomes, to serve as proof that what’s happening in the middle can be trusted and enhanced by the actions of each stakeholder. That same clarity can then be the platform for future investments, improved communication with stakeholders, a more seamless way of working built on confidence in the tech deployed, and heightened end-to-end visibility based on trust in the actions derived from data.
As such, the glass box is the conceptual hub for all critical elements to come together and become visible. The concept has been applied to forecasting and replenishment, where end-to-end considerations all become visible, from seasons and holidays, weather, historical trends, location, and much more. Understanding how each participant plays their role in an AI-driven capability empowers them, enhancing the value of the transformation and reducing the risk of not finding the value.
Five Commerce Functions That Need Transparency
There are five commerce-related functions that need that glass box transparency:
- Addressing the end customer: This aspect accounts for all inventory placement, fulfillment forecasting, and resource and labor planning that will ensure available inventory relative to customer demand.
- Availability: The “how much and where” concern represented by ensuring inventory availability first and foremost, but also compounded by dynamic safety stock.
- Commitments: Referring back to knowing your ATP, commitments point to immediacy and consistency of availability when searching items online, and that same transparency and accuracy when it comes to visible, proposed fulfillment options.
- Orchestration: The processing and tracking of orders at each leg of their journey, with full visibility available to the retailer (and all relevant personnel), any third parties, and the customer as well.
- Fulfillment: Efficient execution must be promoted across and between channels, nodding to areas of store and warehouse availability, pick optimization, labor optimization, and ultimate last-mile integration.
All five of these core commerce considerations comprise numerous strands that retailers often struggle to fully grasp and optimize, due to dispersed or duplicated ownership across an organization. The glass box brings clarity to how the five commerce business functions are connected to the organization.
Lifting the Bonnet
Perhaps that’s what the glass box best symbolizes – a lifting of the bonnet or trunk, under which retailers can see how the parts work together to contribute to the overall engine, while also being offered guidance on how to reap the benefits.
Not so long ago, the types of decisions being made under this bonnet were conducted manually or in silos. It’s taken a cultural shift to get to this point, where experience and expertise is being rightfully complemented and augmented (not replaced) by AI and ML a next level of confidence can be added to this shift, by explaining the parts that nobody can see fully – the end-to-end journey being addressed, and the results they should expect to enjoy based on the inputs offered.
Forecasting demand across channels, delivering on shelf availability both in-store and online, utilizing existing networks effectively to fulfill orders, offering more diverse fulfillment options, and optimally managing that last mile are all upshots that retailers need in the new era of commerce.
Until now, retailers may not have had a full understanding of how to succeed in these critical areas, or whether their AI investments are hitting these specific targets. It’s time to look in the glass box to gauge efforts so far and to fully grasp the role of AI and ML in the future of commerce.
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