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.
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