A new supply chain planning team comprising humans and machines is needed. Why? Because both are required to practice what Accenture calls Applied Intelligence, the application of intelligent technology and human ingenuity to solve complex challenges.
Let’s take supply chain planning for example: Here applied intelligence is essential to not only power efficiency and effectiveness but also to predict and deliver distinct customer product and service needs. For instance:
- Demand signals will come from a variety of sources, including internet-enabled devices, social media platforms and connected channel partners. In fashion retail, data from Instagram can be leveraged to gain early signals of upcoming trends. In telecom, cell phone activation data can be used to better manage channel and spare parts stocks. In pharma, smart packages provide signals about product consumption at the patient level.
- Analytics engines can use intelligence gained from large, unstructured data sets to automatically generate and enrich demand and supply plans. For example, companies are supplementing traditional data used in demand forecasting, such as sales order history and promotions, with information on events, politics, climate change and trending topics in the social media sphere that can all have an impact on demand in the short or long term.
- Optimization solvers that use in-memory and cloud computing can refresh plans in seconds versus days or hours. For example, some chemical companies have invested in solutions to optimize complex supply and production networks based on contribution margin, taking constraints, set-up costs, logistics costs, and even feedstock and finished goods price forecasts into account. A few years ago, even simple volume-based optimization runs could have lasted multiple hours.
- Artificial intelligence that use in-memory and cloud computing can automate significant portions of the planning process while tightly integrating and synchronizing planning with the supply and fulfillment ecosystems. For instance, healthcare providers are incorporating real-time demand information and deviation data captured by production equipment sensors in the planning, production and quality release process to enable continuous responsiveness to changing patient needs.
However, humans also are a critical part of the equation. The supply chain planner of the future will assume greater responsibility across all planning processes of a company. Accenture Strategy sees the traditional demand, supply, production, commercial and financial planner roles likely merging into a single end-to-end planning service function. This group will be responsible for planning multiple different supply chains that meet the needs of specific customer micro-segments, as well as managing business relationships and exceptions.
Concurrently, a new “digital engineer” role will emerge—highly analytical, digitally savvy data scientists who manage, model and tweak the algorithms, alerts protocols and parameters guiding the automated decision-making planning systems. The end-to-end planner and the digital engineer will form a team to make applied intelligence in planning happen. If we take the needs of different customer micro-segments, we can imagine different planning archetypes supported by applied intelligence. For example:
- A lean and reliable approach, where boundaries between planning and supply chain execution diminish—we call it “Plani-cution.” Concepts like demand-driven MRP provide a path to run the supply chain solely on sales orders in real time with great automation potential.
- An agile and flexible approach that is based on an asset-light and collaborative model. Why not apply a concept like Fourth Party Logistics (4PL) to production assets? Here, supply chain planning must evolve from a local firm to a network or platform perspective— synchronizing demand and supply of the connected platform participants.
- An innovation-driven approach that leverages concepts like demand sensing, attribute-based forecasting and advanced customer analytics to predict and supply customers with new product and services.
New planning models are needed to support this vision of a future planning function where humans and machines work alongside each other. Accenture Strategy research found that 83 percent of executives believe their current planning systems still require high to medium human intervention. Sixty-eight percent think new, intelligent software solutions are required to make the vision of end-to-end and rule-based automated planning a reality.1
With new technologies and roles in a place, a company will execute the end-to-end planning process in an entirely new way. There will be fewer, more highly skilled planners working closely with intelligent technologies. The potential business benefits of an end-to-end, digitally-enabled and real-time planning model include an increase in revenue, and reduced inventories, obsolescence and operating costs.
An end-to-end, digitally-enabled and real-time planning model
Despite the significant opportunity, many companies have yet to invest in building the necessary supply chain capabilities. Nearly half of the executives we surveyed said investments in collaboration tools and algorithms to drive higher quality plans could be three years away, with more than one-third predicting the same for real-time analytics.2
Many of these technologies need more than a simple flip of a switch to be operational. There is a learning curve and these technologies also require piloting, tuning and tweaking. Moreover, attracting and retaining the right new planning talent requires a company to rethink its workforce strategy. Waiting three years to invest could mean a company never catches up to early adopters.
Companies must begin working now to plot their course to a new planning function. It is incumbent upon supply chain leaders to ensure they act to shape a positive future for the business and the supply chain planning workforce.
A good start is to define the supply chain and workforce vision for the future, determine the core planning capabilities needed to achieve that vision and identify where and how to begin the transformation. Doing so will help companies get a jump on delivering customized products and services to the increasing number of customer micro-segments that are critical to growth in the years ahead.
1 Accenture Strategy Future of Supply Chain research, 2017