We are entering into a new era where systems are enabled by live, real-time data such as GPS, sensors, mobile, social media, and a connected web of streaming data. Enterprise system designers and operational decision makers are beginning to understand the potential of this continuous intelligence, and think about how to use it in operational decision-making.
Operational decisions — in manufacturing, logistics, procurement, security, risk/disaster management, or other operational domains — are made on a variety of different time frames as illustrated in Figure 1.
Figure 1 – Operational Decision Timeframes
Discussions about operational decision-making processes and systems often focus on planning (strategic and tactical) decisions driving through to execution. These are critical to success. But no matter how good you are at planning and executing, ‘stuff happens.’ This is where real-time decision-making comes in — the moment-by-moment judgment calls made by dispatchers, plant workers, first responders, warfighters, law enforcement officers, logisticians, and their leaders in the ‘heat of battle,’ often out in the field or on the plant floor.1
Making the right moment-by-moment decisions requires good instincts and intuition, but just as critically, it requires continuous situational awareness — a clear, accurate, current, and full understanding of what is going on and what is most important so you can figure out the best course of action. Traditional enterprise systems are not designed to provide continuous real-time situational awareness. Operational decision-making and the enterprise systems that support it usually suffer from the equivalent of the ‘fog of war’ — having an incomplete, imprecise, or out-of-date picture of what is actually happening on the ground. Furthermore, these systems lack the ability to escalate those data points that are truly important for real-time decisions. Sometimes the critical pieces of information are missing, or too late. but at other times they are simply lost in a sea of information overload.
A system providing continuous real-time situational awareness requires:
- Continuous Monitoring — Of the current situation, including location and status of anything that can impact operational success. This could include location/direction/speed of vehicles, weather, traffic conditions, people movement and intent, natural disasters, conditions at various sites, etc. There can be innumerable streams being fed, including sensors, video, social media, governmental data, and various free and for fee data feeds. Continuous monitoring differs from the daily, or batch, or query-based mode characterizing many enterprise systems.
- Precision/Granularity — There needs to be sufficient precision of information for real-time decisions. Enterprise systems usually have ‘transactional’ precision. For example, they can tell you that an order has been shipped or arrived, but not where it is at or the temperature in its compartment at this moment.
- Temporal and Geospatial — Understanding sequence, time, and location of events. Enterprise systems are often not designed to incorporate geospatial and temporal information in a meaningful way. There are systems that are optimized to handle multi-dimensional, dynamic geospatial and temporal data, such as many moving vehicles and complex 2D or 3D polygons (e.g. storm systems).
- Relevance/Escalation — The ability to identify and escalate critical events or pieces of information. Out of potentially millions of data points, pick out those few that really matter in decision-making.
- Synthesis — The ability to synthesize many different streams of data to create a coherent picture. This includes all kinds of data outside of enterprise systems, such as weather, traffic, social media, sensors, etc.
- Timeliness — The ability to do all this within the window of time required to make the decision. After-the-fact has no value in real-time decisions.
- Predictive — Give as much advanced warning as possible of impending events that could cause problems or require a change in planned action.
This range of capabilities does not exist in traditional enterprise systems (ERP, TMS, WMS, SCM, etc.). However, there is an emerging class of systems that is optimized to integrate massive flows of geospatial and temporal data with all varieties of other types of data, with rules engines that can pick out the needle in the haystack, as well as provide predictive analytics, all in split-second time-frames required for real-time decision making. By doing this non-stop, they are able to provide ‘Continuous Decision Intelligence’ for time-critical decisions.
Here are some examples of where these types of situational awareness capabilities can be useful in operations:
- Remote Asset/Facility Management — Increasingly critical machinery, such as power generation, mining trucks, as well as buildings and facilities, are being outfitted with sensors and monitoring devices. These sensor inputs can be made more effective when combined with data about the environment and events around the site, such as current and anticipated weather, people movement, power usage, seismic activity, electricity prices, etc. With continuous situational awareness, the people tasked with managing these remote resources can make smarter decisions such as when to send a crew out to maintain them, when to shut down or implement various safety measures, when to pre-heat or pre-cool a building, when to alert the operator of the equipment that they need to do something different (e.g. slow down, take a different route, bring the vehicle in for repair), etc.
- Real-time Transportation Management — This includes things like awareness of traffic or big events that will create traffic in the near future (like a major sporting event nearing its conclusion), weather, congestion at a port or transloading facility, impactful events on the intended routes (e.g. explosion, riot, flood, etc.), a truck that has deviated from the prescribed route, temperature excursions in a temperature-sensitive load, real-time changes in demand (like a construction delay or change in well drilling progress means that material headed for that site is not needed until next week). Imagine trying to monitor all this for thousands of vehicles, millions of miles of transport lanes, and tens of thousands of locations. Having the situational awareness can help alert to a potential cargo theft in progress, allow re-routing of vehicles, give the earliest possible warning of late shipments, and generally allow for agility in execution not possible without it. (See Transportation Technology Redefined)
- Storm Management — Organizations (public and private) need to respond when a storm is approaching, during the storm, and in the aftermath. Sometimes lives are at stake. Whether it is a manufacturer, a municipality, emergency response team, a retailer, or a power company — all of them need the latest information about everything affecting their operations. Predictive intelligence that adapts with the absolutely most current data enables smarter prepositioning of assets, based on latest available storm information — whether its repair crews and equipment, or supplies that consumers will use before and after the storm. It also allows smarter dispatching of crews and equipment during and after the storm. And ongoing Continuous Decisions Intelligence provides alerts and awareness of where critical needs have arisen that need attention — i.e. more intelligent triage and resource coordination and prioritization.
- Site security — Security systems are already designed to provide a level of situational awareness. However, often these are constrained to the monitoring devices on the site and require constant human monitoring to detect activities. A situational awareness system adds automatic monitoring as well as intelligence from external feeds and other systems.
- Crew Management — The safety and efficiency of crews out in the field (e.g. construction crews, power line maintenance, oil field production crews, etc.) can be improved by providing things like ‘take cover’ alerts when bad weather is approaching, re-routing of crews based on traffic or other potential job disrupting events, and more precise resource coordination when multiple vehicles, equipment, and specific expertise need to converge at the same time and place.
- Manufacturing Plant Monitoring and Control — Plants have a good degree of production-system situational awareness via built-in instrumentation. This can be enhanced by synthesizing data from multiple systems (e.g. receiving, quality, security) as well as external data feeds to improve real-time production decisions.
A good movie director zooms in and focuses your attention on the one thing that you really should be paying attention to right now. In real life, there are thousands of distractions and meaningless data points — only a few of them really matter. A good situational awareness system zooms in on those critical few things and provides alerts that something needs attention. And it does it on time. This is most important in high-value time-critical decisions.
The impact and value of receiving relevant real-time information on time can be enormous. Planning systems and analytics are very valuable, but cannot take the place of real-time Continuous Decision Intelligence. Having the right piece of information at the right time can literally save lives, destruction or damage of critical assets, and millions of dollars from a single decision. More and more organizations will adopt increasingly sophisticated real-time situational awareness systems and approaches as their enormous value and versatility becomes apparent.
1 Real-time decisions are part of the execution process. However, most execution systems support the decisions made just prior to the actual execution-like where to send our trucks today or what will we manufacture today. Here we are distinguishing those from decisions that need to be made in real-time, even though both are part of execution. — Return to article text above
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