Ten Improvements in Data Quality Provided by the Internet of Things
Rick Payne | February 5, 2020 |
Good data quality is the foundation from which accountants provide effective decision-support and business partnering. We have therefore spent a lot of time at recent meetings of the IFAC Professional Accountants in Business Committee thinking about the impact of data and analytics on accountants. For example we have recently looked at the role of the finance function in data valuation and how to build data science and analytics capabilities in finance and accounting.
My focus at the ICAEW over the last year has been the use of data produced by the internet of things (IoT), and how accountants can embrace its potential and look for both everyday and innovative ways to use the data it generates.
The internet of things is the network of devices such as vehicles, machines and home appliances that contain computing power, software, sensors, actuators and connectivity which allow things to connect, interact and exchange data. For example. heavy machinery with sensors that measure vibration, temperature and oil levels can send data to the cloud where it can be analyzed to predict break-downs and schedule preventative maintenance.
ICAEW partnered with the Shanghai National Accounting Institute and Inspur to talk to IT, operations and finance professionals across China, which is playing a leading role in the development of the IoT. The full findings of our research are available in the report, The internet of things and accounting.
In this article, I focus on the ten ways the IoT improves data quality. Many of these improvements are useful in managing fixed assets, inventory, costs, revenues and risks but below are a range of examples.
- Accuracy – radio frequency identity (RFID) tags on stock can be scanned from a distance to give accurate counts and detailed item details.
- Frequency – the calibration of machine tools can be monitored regularly by sensors and adjusted as soon as necessary to maintain output quality.
- Timeliness – vehicle locations can be tracked in real-time through GPS so that traffic jams can be avoided, and customers can be kept up to date with delivery times.
- Objectivity – the actual usage of products and services can be measured instead of estimated through potentially biased surveys, e.g. TV program audience numbers.
- Verifiability – time-stamped audit trails and logs can be generated automatically e.g. when a pipeline has been inspected.
- Reproducibility – motion sensors more consistently measure store footfall than human counters.
- Validity – actual energy usage of equipment can be measured rather than theoretical usage based on technical specifications.
- Granularity – precise quantities of ingredients in food products can be monitored to ensure quality and consistency.
- Uniqueness – placing sensors in new locations or objects generate novel data sets, for example to monitor the impact of climate change across the globe.
- Comprehensiveness – all items, not just samples, on a production line can be quality checked using computer vision and other sensors.
Data from the IoT, along with other forms of big data, could be used to expand the boundaries of accounting and enable accountants to add more value to organizations. The opportunities are clear, and accountants need to embrace them.