Using visibility to boost performance
We have become used to looking at satellite images of the Earth. We can zoom in and focus on the roof of a supplier factory that might be thousands of miles away. But we can't take off the roof and see what's happening inside. We can't tell how much energy is being used just from the satellite image. We can't tell how much water is being wasted just from a drone image. But what if we could? What if the aerial image could be used to look inside and make it visible? To tell us how much energy, water and materials are being used, how much is being wasted, and the levels of waste, pollution, emissions, costs and risk. Imagine if your customer could click on their smart phone and see how much energy and money you are wasting in your business and compare it with others. Visibility at this scale has the potential to stimulate performance and change the way we do business.
Using an aerial image, analytics can be used to estimate the energy, water and materials used by a facility as well as quantify the waste, pollution, emissions and costs. The analytics can quickly identify, quantify and prioritise hundreds of resource and cost saving measures for a facility - opening the way to boosting enterprise and environmental performance. This approach is based on a new area of technology called Remote Digital Twin (RDT) or Distal Digital Twin. The RDT has a conventional counterpart, the Proximal Digital Twin (PDT) with the difference that the PDT is 'close' to the system of interest, generally relying on real-time data feeds from within the facility, whilst the RDT is remote and relies on information from outside the facility.
Proximal Digital Twin
Examples of PDTs (often referred to simply as Digital Twins) are GE's Predix and Siemens Mindsphere. They reflect the increasing level of automation and reach of the Internet of Things (IoT) and Industrial Internet (II) through sensors, actuators and information and communications technology. The PDT provides for deep introspection inside the business using big data streams to achieve a physical and cyber pairing of digital assets. The main focus of the PDT is on asset utilisation and performance often through the life cycle of a product or production line or whole facility. The PDT can extend outside the business as it may use cloud with analytics operated remotely from the facility where the 'things' of interest are located.
Remote Digital Twin
The RDT is very different from the PDT. It does not rely on sensors and actuators and connection to digital systems inside the facility. Instead, the RDT relies on images and other remote sensing by means of drones, satellites, street view vehicles and other systems that work at-a-distance. The RDT access data sources such as weather data and flood maps to support the analytics. Obviously, this means that the precise details of what is happening inside a facility may not necessarily be accessible to the RDT because the RDT is instead viewing the facility (e.g. factory, data centre, distribution centre, corporation, industrial park, city, investment portfolio, insured business) as a whole system and simulating self-consistently the many subsystems that would be expected to be found inside. The main focus of the RDT is on performance, situation analysis, innovation, resilience & growth. The RDT looks both inside & outside the facility to understand the enterprise in its changing landscape and provides insight into business growth, options for change, improved resilience & risk management. It makes extensive use of benchmarking & situation analysis and builds a detailed model of the enterprise based on at-a-distance images.
The Greenclick approach is one example of an RDT and is based on an analytics approach illustrated in Figure 1.
Figure 1. Enterprise model used by the Greenclick RDT.
The RDT creates a model of the enterprise based on primary and secondary activities with detailed analytics of the physical and cyber infrastructures that enable the enterprise to function. The RDT also models the potential IoT stack with which the enterprise can be integrated.
The analytics makes inferences deep inside the physical infrastructure, for example, and classifies the equipment that would be expected to be found inside the facility and from that classification simulates the energy, water and materials flows through the enterprise as well as prediction of production outputs, waste and pollution streams and costs. The RDT effectively provides analytics of the whole enterprise, from the supply side through to the demand side and from the remote (e.g. drone/satellite) imagery and supporting data (e.g. weather data) infers what happens in between the supply and demand sides. This is illustrated in Figure 2 which shows the broader model used by the RDT.
Figure 2. Enterprise model used by the Greenclick RDT showing the supply and demand sides of the facility, resource flows and waste streams that are quantified.
The RDT is inherently different to the PDT in that RDT is concerned with scenarios to assess options. Of course, one of the options that the RDT could assess is the pathway for rolling out a PDT in the enterprise. Generally, options include resource efficiency options (energy, water, materials and cost savings opportunities), technology & business model options (including M&A activity and competitors), building circular systems, new product lines, disruptive events (e.g. power outages, fire, machine breakdown) & climate impacts (hurricanes, flooding, drought). In other words, the RDT can create visibility of an enterprise at any point in the supply chain and evaluate not only its current operations but also predict how those operations may have been in the past and what they could be in the future under different scenarios.
RDT explores resilience
What if there was a utility power outage or some other disruption? The RDT can predict how the facility might respond and how processes and resource use could be affected. By way of example, the RDT scenario analyser can be used to assess how a critical supplier might respond under different events, such as utility blackouts caused by extreme weather events. The nature of the event can be adjusted within the scenario to explore the resilience of the supplier and to investigate implications for costs, energy and other resource usage.
An example is shown in Figure 3 for a critical supplier (of natural rubber) in an automotive supply chain. The upper part of the figure shows the energy usage of the factory over a month estimated by the RDT using satellite imagery under normal conditions. This is the base line for the factory. The lower part of Figure 3 shows the predicted response under conditions of intermittent region-wide utility outages from day 9 as the factory's diesel back-up generator kicks in and production line breakdowns occur from day 16 onwards. From the point of view of the automotive manufacturer, the RDT provides visibility not only into normal operations of a supplier deep within the supply chain, as well as identifying opportunities for energy and other savings, but also provides insight into the impact that loss of production capacity could have on supply-side dynamics. RDTs can serve an important role in helping businesses improve environmental performance through their supply chains.
Figure 3. Upper part: RDT estimate of energy consumption by the natural rubber factory over a period of one month. Lower part: RDT estimate of the response of the factory to utility outages.
Using visibility to make better decisions
Visibility can be used to make better business decisions. For example, in the insurance sector the ability to assess energy and water efficiencies of facilities can be used to inform risk pricing. RDT analytics provide data which are granular and specific, as well as standardised, comparable and benchmarked. The examples in Figure 4 illustrate distributions of insured sites in an underwriter's portfolio.
Focusing on the case of water efficiency (lower part of Figure 4), the underwriter may set different premiums for customer 1 and customer 2 as this would reflect the different levels of effort that the two customers have made in reducing their water-related business interruption risk, particularly if both sites are in operated in drought zones. Water intake and water discharge at each facility can be estimated by the RDT together with costs and CO2e. The RDT also characterise the purposes of re-circulated water as well as the ways in which the discharged water is treated.
Figure 4. Upper part: RDT estimate of the distribution of energy efficiency ratings of commercial sites in the underwriter’s portfolio. Ratings for two customers are shown to illustrate considerations for risk pricing. Lower part: RDT estimate of the distribution of water efficiency ratings of commercial sites in the underwriter’s portfolio. Ratings for two customers are shown to illustrate considerations for risk pricing; both customers operate in a drought zone and are subjected to business water rationing.
Hybrid Digital Twins
Hybrid Digital Twins (HDTs) represent the convergence of capabilities of the PDT and RDT. They bring together the best of both worlds. Their digital systems provide the business with simultaneous perspectives deep within the business, through supply chains & geographies (e.g. cities), across global markets and deep within investment and insurance portfolios. The era of the HDT is expected to facilitate combined asset performance, risk management and business adaptation in fast-changing markets.
When visibility is the enterprise norm
How do RDT's fit into the 4th industrial revolution? In the information revolution we witnessed an increase in visibility of the 'outside' of facilities. Technologies such as Google maps brought capabilities to inspect facilities from the outside - whether it was an industrial facility across the other side of town or a factory on the other side of the world. The 4th industrial revolution will give greater visibility of what is happening on the inside and how that may change. This can be particularly useful when a business is driving large-scale transformations through its supply chain, because having immediate visibility into each supplier can facilitate deeper and more immediate collaboration. The level of information that can be provided to each supplier on Key Performance Indicators and savings can be used to promote better understanding of the many opportunities for improvement, risk reduction and financial savings. Use of the RDT also facilitates improved standardisation, which is helpful not only to Brands but also to investors, insurers and other stakeholders. The RDT can also be used to optimise the way in which auditing is performed, thereby reducing costs as auditing is targeted on risk hot-spots.
As we move further into the 4th industrial revolution, new capabilities in visibility will lay the groundwork for new types and norms of business processes. PDTs, RDT's and HDT's are opening the way to a new world of business in which visibility is the enterprise norm. This is particularly relevant for building high-performance resilient super-sensory enterprises.