Automation is key to IOT scale and cost control


The proliferation of IOT devices and the data they transmit has implications for technology expense management and risk mitigation for IOT.

As key industries become increasingly digitally dependent, IDC estimates there will be 55.7 billion connected internet of things (IOT) devices in use by 2025, generating almost 80B zettabytes of data.

Meanwhile, the GSMA’s Mobile Economy 2021 report says there were over 13 billion IOT connections by 2020, with this number expected to top 24 billion by 2025. By 2023, spending is expected to increase to $1.1 trillion, with South Africa as one of the fastest-growing IOT markets in MEA region, growing at a CAGR of 14% from 2020 to 2025, with growth expected to accelerate through 2028.

Sectors ranging from healthcare, automotive, manufacturing and utilities, through to retail, transportation and public sector are planning to ramp up their IOT deployments – a trend we see echoed in South Africa.

The security and vehicle tracking sectors pioneered IOT adoption locally, but we also see strong growth in the medical, financial, insurance and retail industries. Agriculture is starting to understand the massive benefits connected IOT devices can bring to that industry.

The most common challenge encountered with customers is the absence of a single, automated view that connects all the various data sets.

This incredible growth has huge implications for the storage, processing and analysis of IOT data. But equally importantly, the proliferation of IOT devices and the data they transmit has implications for technology expense management and risk mitigation for IOT − users and providers alike.

You don’t know what you don’t know

IOT service providers to sectors like the vehicle telematics, security and point-of-sale markets typically have to grapple with managing high volume, multi-carrier GSM SIM card estates delivered to customers across a diverse geographic landscape. They might onboard thousands of SIMs in a week, and tens of thousands a year, with potentially devastating financial implications should they be unable to control expense sprawl and properly manage the estate.

In data-rich environments where automation and efficiency at scale are key success factors, there is a need to collate, manage, understand and connect disparate and often complex data sets which are commonly “owned” by different individuals and departments within the organisation’s hierarchy. They can also reside in various applications, servers, portals and/or spreadsheets.

The most common challenge encountered with customers is the absence of a single, automated view that connects all the various data sets.

Some of these common data sets, which often reside in silos and third-party applications, include:

  • Carrier information: Carrier names, MSISDNs, account numbers, tariff names and tariff types.
  • Carrier consumption data: Detailed daily, weekly and monthly consumption/usage records.
  • Carrier invoice data: All fixed recurring and or ad hoc invoice line items as well as variable consumption costs per MSISDN.
  • Customer data: Customer names, locations, regions, branches and cost centres.
  • Product data: Product names, product types and product categories.
  • Device/hardware data: Makes, models, serial numbers, unit metadata, supplier details and stock levels.
  • Financial data: Input costs, sale costs and profit margins.

Not having a consolidated view of all this metadata for management and analysis can have far-reaching and often hidden impacts on customer experience, procurement strategy, profitability, operational efficiency and business continuity.

IOT providers risk unexpected large network charges they cannot recover from client fees, or wasted expenditure due to SIMs connecting across borders or using incorrect protocols.

They also face hidden costs associated with admin and technical resources that need to spend excessive amounts of time identifying and resolving issues. For most customers, it is a case of “you don’t know what you don’t know”.

While many organisations invest sometimes excessive amounts of manual and costly time and resources working with the data to try and extrapolate meaningful information, they are only able to deliver partial insights and limited value back into their respective businesses. This is primarily because this level of data management is typically non-core.

Getting to grips with IOT

By aggregating and connecting the relevant data sets, the organisation is empowered to deliver powerful analytics, reports, dashboards and tools to ensure every IOT device is visible and accounted for in terms of its profit metrics, consumption and associated metadata.

With centralised visibility into all carriers, customers, products, SIMs, products, services and devices, organisations can identify and eradicate double billing, errors and wasted expenditure. They can easily understand cost drivers and profitability per region, per customer, per SIM or per product, simplifying billing, cost allocation and reporting.

In addition to understanding and managing expenses, companies can centralise carrier functionality, such as SIM locks and PIN and PUK retrieval, set business rules and alerts for SIMs, analyse SIM traffic by customer, or by product, to ensure accurate device configuration, and address lengthy connection times, potential time-outs and the use of incorrect protocols.

Businesses are empowered to mitigate a number of risks by better understanding areas such as primary and failover SIM costs and consumption by device. They can also manage the costs associated with stock, such as SIMs that have not yet been deployed and the aligned monthly recurring carrier charges, or cancelled SIMs, to ensure carrier costs are no longer being applied.

Organisations can begin to eradicate single risk dependency on people, manual spreadsheets and home-grown applications, and ensure they are complying with contractual obligations, both with clients and networks.

Original ITWeb Article can be seen by clicking here.

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