Target Value Hypothesis
Before diving straight into the technology solution, any new initiative needs to target a business hypothesis that these new tools could help address. Key questions to address include:
What questions do we struggle to address as a business?
Which indicators would help guide our thinking?
Where is the richest source of insight?
Who needs to know more, or is best positioned to act in response to this information if we had it?
Pinning down and prioritising these questions, with the strengths of connected devices and machine learning capabilities in mind, is the first step to a more responsive organisation.
Connect and collect
Once we have defined a question to answer, it’s time to get started collecting data by connecting devices.
This shouldn’t mean providing a mountain of raw data streams from exciting new sensors. Maintain your focus on the business questions you’ve identified, and ensure the data being ingested and analysed is directed at the hypothesis we’re aiming to gather evidence for.
Machine learning is the key enabler here, taking what might have been a previously unmanageable volume of data, and processing it to be decision-ready. For example, these algorithms could turn a raw camera feed of a retail store - manually analysed by people after the fact - into a responsive feed that includes, at any given moment, live counting, path tracking and group size monitoring of customers in a service environment.
Once data is collected and processed as appropriate, it’s time to trial how well it can inform responses to our targeted value hypothesis.
The most effective applications of collected data are uncovered by putting new information in the hands of those most able to act upon it. This means those on the front line of the business, active on the outer edges, can preempt issues, delight customers or optimise daily operations in real-time on real evidence. This closes the Connected Learning Loop and feeds insight into additional value hypotheses to target.
How your organisation can start learning today
The most exciting thing about this approach is that it doesn’t take a multi-year, multi-million pound programme to start realising the benefits of IoT. Anyone, in any organisation, can get started today.
At Kin + Carta Create, together with Transport for London (TfL), we sought to improve how efficiently the Underground network answered the question: ‘Is there a more efficient way to test the brakes on a Tube train?’ Existing technology was cumbersome, expensive and required a Tube train to be removed from service for testing - resulting in costly disruption to the network.
Over the course of just five days, a small team conducted a technical proof-of-concept that demonstrably proved an iPad could be used to test the brakes of a Tube train as accurately, and much more cost effectively, than existing brake testing technology. Over the subsequent months, the product was developed further and robustly tested alongside the existing solution. The new tool, known as TfL Decelerator, is in pilot phase. Across three lines alone, Decelerator is projected to save £300,000 per year - scale that up across the network, and the savings are considerable indeed. Read more about how we did it here.
Don’t wait to experiment with Connected Learning Loops
You don’t need a mountain of time or money to realise the benefits IoT technology has to offer. As projects like TfL Decelerator show, smartphones and tablets offer connectivity, light, audio and motion sensors that can provide the minimum viable infrastructure for new insights, right out of the box.
All you need is a small and empowered cross-functional team. Give this team a clear question to tackle, and get them to work through the Connected Learning Loop. Ensure they are feeding back lessons learnt as they go, and use it to inform future actions. This lightweight, small scale approach to real-world business challenges enables you to trial new innovations and gain the essential evidence you need to see if it’s worth scaling it across your entire business.
It’s time to get learning, and start earning.