Preventing aggression against front line staff

Reiss Spear, Regional Sales Manager, IDIS Europe

Why automated systems powered by video analytics are proving to be so effective in public settings

Even at the best of times, customer-facing staff need safeguarding from verbal and physical abuse – last year in the UK a survey of shop workers by the union USDAW found that shopfloor staff were abused, threatened or assaulted on average once a fortnight.

And of course, these are not the best of times.

Yes, the 2020 pandemic has seen most people responding well, respecting those around them in public settings, maintaining good humour, and being patient when things get inconvenient.

And most have shared greater appreciation for the work that key workers do: not just health workers, but everyone who keeps essential services running, from warehouse and logistics teams, to retail staff and of course the security officers who help protect them.

But the stresses of the pandemic have also brought out the worst in people: selfishness, impatience, and sometimes, aggression. The aggressors may be a tiny minority, but they have a huge impact on the wellbeing of the workers they abuse.

Mask wearing has been one trigger. What seems a simple common-sense protective measure for most, is deeply felt as a partisan issue by a few. This division is perhaps not surprising in today’s polarised atmosphere, where social media has fanned the flames of conspiracy theories – most notably in the US where tensions are high in the run-up to November’s election, but also elsewhere in the world.

Take this recent survey from the UK: face masks are proving to be “a source of tension for a significant minority,” said Professor Bobby Duffy, Director of the Policy Institute at King’s College London at the end of the summer. He was speaking on the publication of research carried out by Ipsos MORI, based on interviews of over 2,200 UK residents aged 16-75. One in eight respondents at that time said they’d been involved in either confrontations or reports to the authorities over people not wearing masks.

In particular the young, and those who trust social media for information on COVID-19, were more likely to subscribe to conspiracy theories around mask wearing. 81% of respondents believed that face masks helped stop the virus spreading – but still 9% did not.

This puts into perspective the challenge faced by any front-line employee who’s asked to enforce – or even to gently encourage – compliance with mask-wearing rules.

USDAW argues that it should not fall to shop workers to enforce the wearing of face masks.

“They are already dealing with more abuse than normal and this could be another flashpoint,” said general secretary Paddy Lillis recently.

The issue doesn’t just affect staff in retail settings, but those in all public facing roles, from healthcare to transport. Last month the New York Times reported that 170 city transit workers had been assaulted or harassed for asking passengers to wear masks.

Social distancing is another measure – and arguably an even more important one – for breaking chains of COVID infection. Rules about what the distance should be have varied from country to country – with most requiring between 1 metre and 2 metres.

But while social distancing may be less politically and emotionally divisive, it is still fraught with potential for conflict and triggering abuse.

USDAW is right to argue against asking general retail staff to enforce these rules. The skill set and natural aptitude required for that task is specific and specialist, and it includes the ability to de-escalate conflicts.

And yet with enormous financial pressures bearing down on retailers, the hospitality sector, transport companies and transit hubs, it’s simply not practical or affordable to employ additional trained security officers.

So, technology has to be part of the answer – and increasingly it is. Video systems enhanced by AI-based deep learning analytics, and making full use of audio capability, can be used to automate both the detection of non-compliance, and the encouragement of compliance.

People infringing rules are much more likely to change their behaviour when reminders are given in this way, when the message reaching them is polite, remote, automated, and authoritative. There is almost no scope for conflict arising, because there is no authority figure physically present to trigger aggression.

And automated public announcements can be used in a wide variety of ways, targeted to specific settings, situations, and audiences. The tone can be varied, from polite, gentle, and even humorous, right up to urgent and commanding.

In some cases, reverse psychology has even been used. For example, the reported anti-intruder applications announcements have been automated to order ‘remain where you are, the police have been alerted’ – which, of course, had the exactly opposite effect: the intruders fled. This was exactly what the system operators wanted, of course.

Reverse-psychology may not be appropriate in hygiene-enforcement applications, but the example illustrates the huge variety, and subtlety, of messaging available. The point is, once you have a powerful, automated system in place, you can vary and refine your messaging as your needs change.

The video technology underpinning these automated solutions is increasingly powerful, and offers great value compared with the cost of employing security staff.

It can be used to detect when people are not wearing face masks, and it can trigger automated verbal or visual reminders.

It can be used for occupancy monitoring in specific and targeted areas, for example detecting when particular aisles are becoming over-crowded. Linked with signage or ‘traffic light’ systems, video analytics can also be used to control automated queuing and admissions to premises, again taking the strain off staff.

These solutions aren’t just less expensive to operate, they represent a solid investment in infrastructure that will deliver value into the future.

And right now, they could save organisations much greater hidden costs in terms of rising staff turnover, and falling morale, in the face of stressed, anxious, and aggressive customers.

In the tough months ahead, video solutions with AI deep learning analytics will help take the strain.

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