How Sustainability is Leading to Disruption in Today's Supply Chain
Sustainability burst onto the scene ~10 years ago as the price of oil shot past $100 per barrel and the discussion on CO2 concentrations in the atmosphere moved from science labs to the board rooms. The increased dialogue on the environmental impacts of business was a positive development. However, the core tenet of sustainability - optimizing usage of resources - has always been about minimizing costs and maximizing financial performance.
Today, the explosion of data powered by the proliferation of smart sensors, or the Internet of Things, has rapidly raised the competitive bar. It is no longer enough for companies to add insulation to their factory walls and plant gardens on their roofs. To win, they must also embrace big data in a way that stitches together fragmented, custom e-commerce orders with reactive, optimized supply chains and factory production.
This blog post explores the framework enterprises can adopt to be sustainable and deliver on Industry 4.0 targets.
Identifying the benefits of going sustainable
By some estimates, 40% ($36 trillion) of the world's revenue is generated by enterprises that consider 'energy cost and energy source' of strategic importance to their production lifecycles. Of this, 27% of the enterprises are in energy-intensive industries where energy costs account for over 5% of their production lifecycle.
Given the scale of these numbers, improving energy usage by even a conservative 2% has the potential to reduce a whopping $30 - $50 billion from corporate cost structures. Additionally, energy prices are notoriously volatile, giving firms one more reason to reduce this line item and achieve greater margin predictability.
Let's take an example. Imagine knowing the cost of making each unit of a product, say a light bulb or a car. Monitoring energy usage throughout the production lifecycle for a single unit provides data about raw material and energy costs.
Surprisingly, very few firms have this knowledge. Yet with such knowledge, it is possible to make strategic decisions about what time of the day to manufacture the product (when energy consumption is at its cheapest) and when to buy additional energy to manufacture bulk orders of that product. Here, enterprises can use integrated weather forecasting tools to understand when to buy additional, cheaper, renewable energy on the energy exchange market, when the sun is shining, and; even modularise production to maximise the energy potential of a given production line.
As a long-term objective, such knowledge can also drive strategic decisions around investment in own energy production, namely, through solar, wind or biomass. This is particularly relevant for highly energy-intensive industries such as mining.
Where firms are today
With the Industry 4.0 initiative well underway, Infosys Consulting decided to find out how firms in Germany were addressing the energy costs in production. Surprising, 85% of firms acknowledged the potential benefits of energy optimization. But only 15% had actionable strategic initiatives in place to realize these benefits. Fortunately, there is a solution here by way of The Infosys Consulting Value Realization Management (VRM™) Framework.
The Infosys Consulting Value Realization Management (VRM™) Framework
This framework helps enterprises translate strategy on energy consumption into actions that can be measured and valued.
To implement VRM™ enterprises first define change initiatives that align with corporate strategy. Then map them to operational processes that can trigger the desired change. These process changes are attached to KPIs that measure overall impact. Ultimately, these operational KPIs are translated into value drivers to quantify the contribution of these changes to financial performance.
To give an example, let's consider the German organization Osram. In February 2017, Dr. Olaf Berlien, CEO of Osram, noted in his address at the annual general meeting that the company wanted to leverage innovation to open new lines of business in support of energy-efficient smart cities. This aspirational statement serves as the strategy component of the VRM™ framework.
Translating this strategy into process changes required supply chain modularization and the installation of predictive analytics to measure equipment downtime. This introduced energy efficiency within both the production process and the end product − supply chain planning, production planning, and procurement.
The corresponding operational KPIs to measure these process changes were: lead-time between first client contract and first order completion, asset downtime and planning accuracy (%) of production lifecycle.
Translating these KPIs into value levers would quantify increased capacity utilization and operational cost reduction, which would impact the enterprise's financials through increased product margin and a reduction in both cost of sales, general and administrative expenses. It would also support the sustainability strategy that translates into a triple bottom line: reduced costs, increased margin, and decreased carbon footprint. By following this framework, companies can measure relative progress at each step of the journey and incrementally course-correct as needed.
Where sustainable supply chains are headed
At their core, many Industry 4.0 advances are being powered by the Internet of Things. Here physical systems contain connected sensors that share data. This dynamic, in which factory 'command centers' are tethered to the cloud, enable real-time monitoring as well as demand-driven configuration. Additionally, supply chains flexibly optimize themselves based on changes in demand or production capacity, and energy is delivered in an optimized manner.
These concepts, which would have seemed the stuff of science fiction just a decade ago, have become standard table stakes in a world where virtual shopping for customized objects has become the norm. Under this paradigm, it is no longer enough for enterprises to produce thousands of the same product. Shoppers now expect personalization, which in some ways is a reversion to manufacturing's roots -- akin to a blacksmith crafting a plow blade for a farmer whose equipment he knows intimately - but at massive scale and in near real-time.
To serve the demanding customer of tomorrow, enterprises must harness their data in ways that allow them to not only keep up with orders, but to optimize their use of resources and keep the costs of personalization in line with their margin expectations. Those that do, will not only help the environment through decreased energy usage, but will also please shareholders via expanding enterprise value - economically and sustainably.