How Are Tech-Enabled Audits Improving Operational Visibility?

Mila Budeva
Mila Budeva
Jun 22, 2017

The advancement of automation and mobile technology is disrupting how operational audits are performed. 

Instead of sending boots on the ground every time they need to review the effectiveness,efficiency and compliance of practices and processes, organisations – from retail stores, through CPG factories, to nuclear operators – can use their digital eyes on the ground.

Drones, robots, data analytics and algorithms have the potential to generate continuous operational visibility, transforming the concept of an audit from a post-hoc snapshot to a real-time predictive capability. The potential to reach even more inhospitable and inaccessible or hazardous areas also improves radically.


Today we look at examples of how tech-enhanced auditing improves audit accuracy and real-time visibility, reduces operational costs, increases safety and uses the data collected to identify patterns and pre-empt non-compliance and risks.



In one audit, a single drone has the capacity to collect more, and more accurate information than a team of people might do over the course of several visits. This way human audit teams can shift their time away from mundane and towards value-adding tasks. Drones are particularly efficient when auditing vast or limited access areas, improving visibility and reducing safety risks for human teams. For example, drones have been used in cell tower audits. Instead of sending a 2-5-person team (with their 50 pounds of climbing gear!) to audit the site before future equipment can be installed, the company can send a drone. The drone can make the necessary measurements, record images of the existing conditions and feed back to the human team in real-time so they can focus on the installation work [1]. In another example, EY have launched a global proof of concept to use drones for inventory inspections in warehouses. Drones scan QR/barcodes or  read rack labels and feed back into the audit platfor in seconds, enabling quicker and more frequent audits [2].



Similarly, robots can be used to audit locations which are too dangerous, vast or small for humans to access, providing organisations with otherwise unattainable insights. For example, robots have been sent to inspect the Fukushima nuclear reactors where radiation levels make human inspections impossible.  The Kamuthi Solar Power Plant – the world’s largest solar power project covering an area of 2,500 acres – provides another example. In Kamuthi, robotic systems are used to maintain the solar panels, preventing energy generation drops caused by dust storms [3]. Robots can also be made small enough to inspect pipelines and tubes, preventing costly and time-consuming manual excavations. GE Hitachi, for example, have developed robotic systems which can traverse pipes with a diameter as small as 6in and can travel up to 1,000 ft. in empty or liquid filled pipes [4].

Robots are not only designed to replace humans in hazardous or inaccessible areas but to also work beside them, automating mundane, repetitive tasks. For example, Tally audits shop floors for out-of- or low-stocks, misplaced or mispriced products during opening hours, alongside human employees and customers. This way store associates can focus on value-adding activities such as serving customers, up- and cross-selling [5].


Predictive & Prescriptive Analytics and Smart Sensors

Analytics engines and algorithms, processing the data collected by audit tools, help to improve the precision of data analysis. This way, tech-empowered audits not only improve the speed and accuracy of the data collected but also enable the identification of patterns and the pre-emption of risks and non-compliance. A Manufacturing Execution System, for example, automates performance and quality data collection on the shop floor and provides manufacturers with real-time visibility over all steps of the production process. Data is analysed in real-time and predictive maintenance alerts about inefficiencies and issues can be pushed to employees on the shop floor.  This way, manufacturers can immediately implement corrective action and continuously improve Overall Equipment Effectiveness (OEE).

Data captured about issues, root cause and corrective actions taken then feeds back into the analytics engine, helping to continuously refine the accuracy of algorithms, predict inefficiencies and prescribe the best course of action. Prescriptive analytics, using optimization and simulation algorithms to advice on possible outcomes, can enable retailers to prevent stock-outs by processing data from sources like POS and inventory systems and generating re-stock alerts to store staff’s mobile devices.  

Similarly, smart sensors can measure input from the physical environment, process and communicate the data to other IoT connected devices.  QSRs, for example, can ensure HACCP compliance, with smart temperature sensors continuously measuring food temperature and any deviation from the standards triggering an alert on workers’ mobile devices.


Image Recognition

Retailers can use image recognition (IR) to audit promotional and planogram compliance, on-shelf availability and pricing more quickly and accurately. For example, retailers can place cameras on the inside of fridge doors. The IR system then captures and analyses an image of the fridge shelves every time the door is closed, checking on-shelf availability and pre-emptively pushing re-stock alerts to store associates to replenish and merchandise shelves.

Healthcare also offers an example of how IR can help to ensure medication safety and adherence. Visiting nurses can take a picture of the patient’s tablets for the day. Instant image analysis checks whether these are the right kinds and quantities of medication, reducing regimen assessment time and eliminating the risk of manual mistakes [6].


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