As key industries become increasingly dependent on digital technologies, IDC predicts that by 2025 there will be 55.7 billion Internet of Things (IOT) connected devices, generating nearly 80 billion zettabytes of data.

Meanwhile, the GSMA’s Mobile Economy 2021 report estimated that there were more than 13 billion IoT connections by 2020, and this number is expected to exceed 24 billion by 2025. Spending is expected to increase to $1.1 trillion by 2023, with South Africa among the fastest growing. – growing IOT markets in the UK MENA region, growing at a CAGR of 14% from 2020 to 2025, with growth expected to accelerate by 2028.

Sectors ranging from healthcare, automotive, manufacturing and utilities, to retail, transport and the public sector are planning to increase their IOT deployment – ​​a trend we are seeing in South Africa.

The security and vehicle tracking sectors have pioneered local IOT adoption, but we are also seeing strong growth in the medical, financial, insurance and retail industries. Agriculture is beginning to realize the huge benefits that connected IOT devices can bring to the industry.

The most common problem customers face is the lack of a single, automated view that connects all of the disparate data sets.

This incredible growth has huge implications for IOT data storage, processing and analysis. But just as importantly, the proliferation of IOT devices and the data they transmit has implications for managing technology costs and reducing risk for users and providers.

You don’t know what you don’t know

IOT service providers for sectors such as vehicle telematics, security, and point-of-sale markets typically have to contend with managing large numbers of multi-carrier GSM SIM cards delivered to customers across different geographic landscapes. They can connect thousands of SIM cards a week and tens of thousands a year, with potentially devastating financial consequences if they fail to control rising costs and manage assets properly.

In data-rich environments, where automation and efficiency at scale are key success factors, there is a need to collect, manage, understand and connect disparate and often complex data sets, typically owned by different individuals and departments within an organization’s hierarchy. They may also reside in various applications, servers, portals, and/or spreadsheets.

The most common problem customers face is the lack of a single, automated view that connects all of the disparate data sets.

Some of these shared data sets, often found in silos and third-party applications, include:

Operator information: Carrier names, MSISDN, account numbers, tariff names and tariff types.

Operator consumption data: Detailed daily, weekly and monthly consumption/usage records.

Operator invoice data: All fixed recurring and/or ad hoc invoice items and variable consumption costs on MSISDN.

Customer details: Customer names, locations, regions, branches and cost centers.

Product details: 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, selling costs and profit.

The lack of a consolidated view of all this metadata for management and analysis can have far-reaching and often hidden consequences for customers, procurement strategy, profitability, operational efficiency and business continuity.

IOT providers run the risk of unexpectedly high network charges that they cannot recover from customer charges, or wasted costs due to SIMs connecting across borders or using the wrong protocols.

They also face the hidden costs of administrative and technical resources that must spend too much time identifying and solving problems. For most customers, it’s a case of “you don’t know what you don’t know”.

While many organizations invest sometimes inordinate amounts of time and resources manually working with data to try to extrapolate meaningful information, they are able to return only partial information and limited value to their business. This is primarily because this level of data management is typically non-core.

Meet the IOT

By combining and connecting relevant data sets, an organization is empowered to provide powerful analytics, reports, dashboards and tools to ensure that every IOT device is visible and accounted for in terms of revenue, consumption and associated metadata.

With centralized visibility across all carriers, customers, products, SIM cards, products, services and devices, organizations can identify and eliminate double billing, errors and wasteful spending. They can easily understand cost drivers and profitability for a region, customer, SIM or product, simplifying invoicing, cost allocation and reporting.

In addition to understanding and managing costs, companies can centralize operator functionality such as SIM blocking and PIN and PUK acquisition, set business rules and alerts for SIM cards, analyze SIM traffic by customer, or by product to ensure accurate device configuration and address long connection times, possible timeouts, and use of incorrect protocols.

Companies can reduce a number of risks by better understanding areas such as primary and post-SIM costs and device consumption. They can also manage inventory related costs such as SIMs that have not yet been deployed and agreed monthly recurring carrier charges or canceled SIMs to ensure that carrier costs no longer apply.

Organizations can begin to eliminate single-risk dependencies from people, manually created spreadsheets, and proprietary applications, and ensure they meet contractual obligations with both customers and networks.

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