How to Enlist Big Data to Drive Additional Revenue Streams
Stanley Security’s Brad Humphries shares how to utilize Big Data to drive additional revenue streams, profits and efficiencies.
Lately there has been a lot of discussion about artificial intelligence (AI) and machine learning (ML) and their potential role as resources for the security industry. From client interfaces, data mining, data processing and monetized services, all have been considered with regard to how they will impact the security business in the coming years.
With the massive amounts of client information that is available, how can security customer preferences be set and tracked by systems integrators and their end users to determine the best use for this Big Data?
In determining what this means for the security industry and to harness such potential, there are two focuses to consider from both integrator and user perspectives — internal and external.
Internally, what can Big Data do to drive efficiencies and profits in day-to-day business; and, externally, how can the information be directed to add revenue streams or increase profits?
Get More From Your Labor Force
The main consideration for internal use is: how can AI drive business intelligence (BI) into everyday operations while still adding value to your customers? The largest asset to be considered is also one of the biggest challenges: finding qualified labor resources.
With low unemployment rates nationwide, along with the increased technology complexity within the security industry, how can BI be leveraged to increase efficiency and capacity within existing labor? The simple answer is to focus on the efficiency of your service teams to increase volume.
Can BI match current technicians’ skillsets, locations and availability to on-demand service needs better than what is happening today? This is most likely the case, within the context of processing data faster around current labor demands within supply capacity constraints.
Imagine being able to drive a 20%-30% efficiency increase in service teams and what that would look like for existing customers, as well as the performance implications for potential customers.
AI engines that are integrated into business systems can help support a systems integration company’s administration team to be able to schedule and respond to customer requests — using all of the raw data, at hand, and turning it into actionable information.
Put Actionable Information at Their Fingertips
For the same reason BI should be an active part of an integrator’s business strategy, your customers are searching for the same edge externally to deploy within their own business strategies.
Close inspection of employees’ daily and weekly actions — while being able to interpret and predict the actions of end-user customers — is paramount to driving efficiencies.
With the massive amounts of data available to track customers’ interaction on webpages and apps, for example, it is a leading factor in being able to identify customer actions in real-time.
Other trackable activities that can be facilitated by data-rich security systems integration include: being able to staff on-demand for peak times vs. lull times; tracking sales data in real-time to catch internal theft; and accessing real-time sales information.
Sharing this supply chain data with distribution centers creates opportunities for customers to interface their video, POS and intelligence systems into a singular dashboard to streamline their information and yield better decision-making.
Some of these technologies have been around for a while, but the critical event that merges this information comes from the use of AI and ML to create enhanced business intelligence.
This can be sourced through all of the available information collected in CRM, monitoring and financial platforms to help drive efficiency of operations, as well as the enhancement of life safety and the protection of property. This technology helps forge long-term business partnerships with customers.
Boost Relationships With Satisfied Customers
Enlisting AI and ML to enhance business intelligence capacity makes sense when comparing the levels of performance required to do the same amount of work during the same amount of time.
The ability to integrate the Big Data that is available within the video surveillance, access control and other systems used every day allows for exponential improvements to be made in responding to customers’ daily operations needs.
Specifically, the speed to serve, along with constant efforts to improve customer satisfaction, have always been the hallmark of security companies that have consistently stood the test of time.
As changes continue to take place with technology, combined with the demographic shifts in society, being able to fully utilize strategic information to help increase efficiency — while offering enticing new solutions to customers — can create real-time, actionable information and enhance the value proposition of security system designs.
This allows systems integrators to transform into data-driven solutions providers that will now serve and be considered as trusted partners for their increasingly happy (and loyal) customers.
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