The Internet of Things (IoT) is just that; it is the connectivity of ordinary things.
The connectivity of the internet, the move to the cloud and big data analytics, combined with the emergence of processing power at the edge, have all allowed products to become connected and smart.
With an expected 20.8 billion connected things to be in existence by 2020, these devices are producing data at an astonishing rate.
The IoT is having an increasing, and possibly disruptive, impact on our lives, in turn influencing and simplifying daily tasks.
Whether this be our phones turning on our home lighting, connected watches monitoring our daily activity levels, driverless cars or automatically replenishing fridges.
Connected devices are also impacting our daily decisions, both in the office and personally, with automation increasingly replacing tasks, some for the better, some arguably not, and these devices are a key contributor to what is now a massive IoT ecosystem.
According to research by the Centre for Economics and Business Research (Cebr) big data analytics and the IoT are expected to add some £322 billion to the UK economy between 2015 and 2020.
This is twice the size of the combined education, NHS and defence budgets for 2014-15, and 22% of the UK’s net public debt (circa. £1.5 trillion in 2014-15). This figure shows the enormity and impact the IoT has had on the UK’s digital revolution.
The impact is more acutely felt amongst finance and professional services, where big data and enhanced productivity tools are increasingly empowering financial directors, financial advisers and accountants to move away from the time consuming, mundane, number crunching tasks.
Doing this allows them to focus on strategic and client-handling related work that helps to generate new business and business growth.
Because of this. automated processes taking over some of the administrative tasks is becoming increasingly popular within the finance profession.
Algorithms delivering value for businesses
Algorithms are the key behind the successful running of our everyday products, from filling in online tax returns to trades on the stock exchange and transferring money.
Algorithms will, in turn, create our economy’s secret weapon of success and mass destruction in equal measure, if the risks aren’t mitigated.
Behind the invisible cogs lies hidden value.Peter Sondergaard, Senior VP of Gartner said: “Data is inherently dumb – algorithms are where the real value lies. Algorithms define action”.
Knowledge is power, and algorithmic data analytics unlock that power, allowing businesses to maximise data driven decision management. In turn, they can keep apace within a competitive landscape, where an ill-informed decision could be costly to both reputation and profitability.
An important area to address is that with the booming algorithmic economy that has been created around IoT, there also comes an increased risk of cyber attacks. Individuals with malicious intent could tamper with algorithms and essentially bring a business to its knees.
Ensuring robust security measures is crucial when developing algorithms, to prevent malicious attacks that can destroy a company’s reputation. The complexities of today’s threats means it is no longer viable to simply add on a security layer at the end and rely on testing just before the project goes live – this approach is too little, too late.
Additional pressures from the IoT revolution
Hardware manufacturers are having to change their strategy and start building hardware around software, rather than treating it as a traditional add on later down the line.
IoT also has the added layer of complexity wherein the device often needs to be able to communicate across a variety of different platforms, such as 5G, Wi-Fi and Bluetooth.
This has forced companies to think more like IT professionals than manufacturers, encouraging the adoption of a ‘software first’ approach.
Need to embrace robust security measures into product life cycles
Companies, traditionally built around the physical manufacturing of their products, already have knowledge of how to test them from a hardware perspective, for example testing a braking system on a car. However, they are not used to having to test software processes that integrate with the hardware, other software from their supply chain and external data sources.
The alternative to releasing untested software onto the market is, at best, embarrassing, but at worst could be catastrophic. Just last year, automotive giant Tesla was forced to issue a software update twice in a month after two researchers found a way to subvert its on-board system. Likewise, if an individual could access the financials for a company ahead of a full year results announcement allowing them to do some insider dealing; or hacking into someone’s personal accounts, the end outcome could be disastrous.
Need to embrace robust software Test and Validation into product life cycles
Given the importance of security in today’s interconnected IT landscape, most software development lifecycle models require security checks to be present at all stages.
Doing this ensures security is baked-in from the beginning, but we also need to recognise that security is not a static attribute of quality. Once software is released, its security must be continuously reviewed to ensure it is not affected by newly discovered vulnerabilities.
By doing this, businesses will unlock the true benefits of the increasingly algorithmic economy, whilst mitigating the risks.
The opportunity that IoT presents for senior figures in finance is too big to miss out on.
Security measures must be put in place to not only safeguard consumers, but to protect brand reputation and avoid losing out to competitors.
There is clearly a role for the IoT to positively transform the traditional FD role as we know it, as automation and increased connectivity help drive time and cost efficiencies.
René Gawron is CFO of SQS Software Quality Systems, AG.