News, Insights, and more on Industrial IoT
Managed Services business models have become much more prevalent over the last few decades thanks to advances in cloud computing technology. More recently, Managed Services Providers (MSPs), in particular, have grown increasingly popular as companies try to optimize operations and decision-making around data streams.
So, what are Managed Services, exactly?
Tech Target defines a Managed Service Provider as “a company that remotely manages a customer's IT infrastructure and/or end-user systems, typically on a proactive basis and under a subscription model.” Usually this model also implies that “the provider's service is supported by a service level agreement (SLA) and is delivered over the internet.” This business model has typically been applied to cloud computing services and IT infrastructure, but that is now extending into the remote asset management world into IoT.
Managed Services for IoT, then, defines a business model in which a vendor proactively supplies IoT data streams to end users, where the quality and veracity of the data is guaranteed under a Service Level Agreement (SLA). This model, like its predecessors in IT and cloud computing, eliminates the need for organizations that require IoT solutions to become experts in data creation, data transport, data management, data storage, and data visualization.
Today, many companies across a variety of industries pay managed service providers for remote services ranging from server and network management, database management, security management, or other managed services. Hewlett Packard, for instance, offers a “Managed Printing Service” where they supply the necessary maintenance and automatic ink-reordering through it’s “Instant Ink” offering. Rolls Royce is famous for making the switch to a Managed Services model for its jet engines in 1962, where it transitioned from making capital-intensive hardware sales to selling “miles flown” with their engines.
Many Managed Service Providers also offer templatized product offerings on top of open architectures, which offer tailored applications to customers without the hassle of employing consultants or system integrators. This applies to traditional MSP models, as well as the IoT model.
The key differentiator to the Managed Services model, regardless of industry or application, is the Service Level Agreement. If you use a cloud service provider to host your company’s data, for instance, they probably provide a service level agreement on data availability and uptime. Under the agreement, the service provider is contractually obligated to respond to and repair downtime events within a certain timeframe, or otherwise provide credits to end customers. The Service Level Agreement gives the end customer the peace of mind that the profitability and success of the vendor is tied to their own success as a customer.
The result of a managed services business model is that the end customer doesn’t have to worry about the fundamental infrastructure or expertise of managing components which power their business operations, and take the risk on the capital expenditures to gain and establish expertise and operational excellence.
Companies who pursue IoT projects typically do so with a vision of establishing a data-driven culture, where employees utilize quality real-time connections to monitor, control, automate, and optimize physical machines and equipment and drive better business outcomes.
This transition presents tremendous challenges to companies just beginning this journey, and as McKinsey pointed out in 2018, nearly 9 out of 10 industrial IoT projects fail to make it past pilot phase.
There are plenty of reasons why.
Industrial workforces are less tech-savvy overall, but for good reasons. Employees are hired to perform heavy engineering work, much of which involves physical labor, not to manage databases and cloud interfaces. Workers in this sector are less likely to understand how to optimize newer technologies and manage complex data streams because they focus their energy in other critical areas, like operational excellence and safety.
Operational technology has survived as long as it has for this very reason. Industrial organizations are slower to adapt because their people simply don’t have the time or capacity to become data professionals. We see this dynamic reflected in workforce demographic data.
According to the U.S. Bureau of Labor Statistics, the median age of the Manufacturing sector was 44 years old in 2019, two years older than the median age of the total U.S. workforce. For sub-niches, such as Machinery Manufacturing and Metal Manufacturing, the median age is slightly older. For further comparison, the median age in the tech industry is 38 years old.
Industrial workforces are trained to manage physical assets, not digital data pipelines. Adding IIoT technologies and infrastructure on top of a full workload involving major physical, mechanical, and electrical processes is out of the question.
Given these realities, industrial organizations must consider other solutions when it comes to maximizing the value of data. However, many forego the Managed Services route in favor of a lesser option.
Because IT expertise is not a core competency for most industrial organizations, they end up hiring system integrators (SIs) to assist in their digital transformation. And most leaders understand that this comes with tremendous cost pressures.
When companies bring on SIs to set up data infrastructure, they pay a premium for both the components of the system and costly integration fees. System integrators tend to resell IIoT devices from original equipment manufacturers (OEMs), so customers end up paying not only for the profits of the OEM at each layer, but also the markup of the SI. On top of that, the businesses will incur systems integrator fees for ongoing maintenance, upgrades, and configurations.
Those who work with systems integrators to digitize physical infrastructure invest enormous sums upfront without any guarantee of future value, which is another reason why operational technology has lagged. The cost of integrating and upgrading new systems constantly is too high to justify.
The SI route also puts pressure on organizations to adopt data-driven cultures, which rarely happens. To justify the high capital investment of digitizing, leaders force their workers to conform to new, complex protocols. These individuals become immensely frustrated as they lack the support and expertise needed to be successful. They feel misunderstood and resentful towards the new technology, leading some to intentionally sabotage digital systems in order to justify returning to the status quo. By adding the pressure to transform into a data-driven organization overnight, organizations create tense workplace environments, which is not healthy for those undergoing massive changes.
IoT Managed Services allow organizations to overcome both the cost and operational barriers associated with sensing, creating, digitizing, managing, and visualization critical operational data from their equipment and machines
The goal of Managed Services for IoT is to eliminate the effort and complexity that organizations typically must undertake in order to establish and execute digital transformation initiatives which leverage IoT technology. Managed Services break down the capital expense barriers to start and upgrade equipment, networking, and software, and they reduce or remove the need to employ native expertise, hire consultants, or contract integrators and installers.
What’s more important, Managed Services for IoT delivers guaranteed data quality under a Service Level Agreement. Higher-quality data results in more inherent trust in the system which generates it, which fosters the data-driven culture that organizations so desire. At WellAware, we believe the Managed Services model is the best approach to creating positive outcomes from IoT digital transformation projects.
With MSPs, workforces don’t have to be data experts. Operators don’t have to worry about the complexities of setting up data collection at the edge, transport, and management in the Cloud. Companies can transition to data-driven cultures without overwhelming employees. Perhaps most importantly, they don’t have to spend so much money to upgrade from OT to IT.
IoT Managed Services create an alignment between value creation and vendor profitability that doesn’t exist under the legacy systems integrator approach.
When it comes to the Industrial IoT, Managed Services vendors are responsible for managing the complexity of creating data connections between a customer's physical assets and their employees and partners. For example, vendors:
Without IoT MSP vendors, industrial organizations have to purchase or invest in these capabilities separately and then unfortunately become experts in an area that should not be a core competency. Instead, they can rely on Managed Services partners to produce high-quality, usable, and meaningful information sets that help industrial organizations make better decisions to monitor, control, and automate equipment.
WellAware is the partner that organizations need to thrive in the digital age. We empower companies to be safer, more efficient, and more sustainable by streaming analytics-quality data between workforces and assets. Our end-to-end approach increases data quality while reducing data transport and storage costs.
We monitor, control, automate, and optimize commercial and industrial equipment using modern, cost-effective technology. Our sensors can connect to almost any make and model of machinery, enabling businesses of all types to take advantage of the IoT.
We also structure data from numerous remote devices to facilitate unified use and consumption. Contrary to how many industrial data vendors operate today, we guarantee data quality under Service Level Agreements and provide all products and services under a level subscription plan, eliminating the barriers and pressures of upfront capital expenses.
WellAware clients also have access to premium support and data analytics expertise at no charge so that they have ample opportunity to create data-driven cultures without burdening their workforces. Our clients enjoy all the benefits of rich, automated data streams without any of the downsides that typically plague industrial businesses.
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