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How can an IOT strategy assist in measuring, managing business productivity, and ultimately translate productivity into profitability?

Johannesburg, 24 May 2019
Read time 8min 20sec

The Internet of things (IOT) is reshaping the world as we know it. From leisure to business to how we clock our hours at work. Interconnected devices in our homes, in our cars and at the office are making our lives easier, faster and more productive in myriad ways.

The IDC predicts that by 2020, IOT endpoints or connected devices (ranging from smartphones and networked entertainment devices to automobiles, building automation systems, smart meters and thermostats, medical electronics and industrial controllers) will reach 30 billion, representing an annual growth rate of 19.2% (Fig 1).

Many consider the IOT to be the next industrial revolution. And, as with any revolution, it brings with it radical changes and most certainly a paradigm shift in respect of business productivity and workflow automation and how these are measured.

With the rapid growth in the number of connected devices, the potential of IOT has scaled substantially. IOT can be defined as an extension of existing connections between people and devices (smart devices, computers, etc) connected to a central control system aimed at, among others, measuring data and reporting on such data. Data in this context can be simple numbers, measurements, periods of time, or data that is more complex, such as simultaneously reporting on multiple data streams.

It must be pointed out, however, that "IOT isn't just about connecting machines to the cloud. It's about connecting your machines to your enterprise and creating a central system of intelligence. It's about aligning your internal operations and teams with your product offerings and giving your business a distinct competitive advantage."

With a proper IOT system, manufacturers can maintain a real-time view of inventory by linking shelves, forklifts, pallets and equipment using sensors and wireless communications. When you attach sensors to, for example, machines and bins on the factory floor, it can provide real-time data on inventory consumption and trigger automatic refills or orders, much like the example of the retail store above. The benefits of this approach include keeping inventories lean and reducing waste. For farmers, IOT can optimise and simplify many of the steps involved in caring for their livestock, such as monitoring each animal's health, movement, location and fertility. The data obtained from this can be analysed and used to increase farm efficiency, productivity, and ultimately, profitability.

In a retail environment, IOT can streamline inventory management and render operations more efficient and profitable. As the retail market increasingly competes with online stores, IOT innovation can assist in enhancing the shopping experience for customers while seamlessly connecting the front and back office. In addition, it can boost efficiency and increase the focus on customer-centricity.

For the majority of IOT users, improving productivity and efficiency is the main focus when considering their IOT strategy. It is therefore crucial that the product you choose to introduce into your specific industry must be able to translate data into something tangible and useful in order to have a real benefit to the company.

According to Richard Barry, CEO of Polymorph: "Workflow automation should form the basis from which IOT can operate. A well-executed IOT strategy leveraging the power inherent to IOT should be able to solve day-to-day processes such as automating manufacturing processes remotely, optimising production processes, managing inventory, and diagnosing repairs and maintenance issues on machines." Barry highlights a few important aspects of an efficient IOT strategy:

Moving data from equipment into the cloud

This is the point of departure for the majority of IOT projects. Moving data from your machines into the cloud depends on the complexity of the machinery, the diversity, velocity and the amount of data produced. Further considerations include the condition of the environment and the networks in which they operate; moving data from your machinery into the cloud can therefore be straightforward or extremely complex. It ultimately depends on identifying the right technologies and applying them appropriately.

Recognise the value of the data

Collecting data from equipment and accurately analysing it enables businesses to become more data-driven. However, the obstacle experienced by many businesses is gaining access to the data. According to Edd Wilder-James, Open Source Strategist at TensorFlow: "The biggest obstacle to using advanced data analysis isn't skill base or technology; it's plain old access to the data." Moreover, even if businesses overcome the challenges associated with data collection, they still fail to deliver systems that can drive the business forward.

Analyse the data so as to provide real value

Collecting data does not only refer to machine data. The McKinsey Global Institute explains that the "greatest potential for creating value from the IOT for manufacturers will be in operations optimisation, making the various processes within the factory more efficient. This includes using sensors, rather than human judgment (and human error), to adjust the performance of machinery."

A sensor may warn of a potential malfunction or alert a supervisor when a machine malfunction occurs, but if your IOT system cannot combine this data (such as temperature, service history, etc) and produce an informed course of action, you might as well use warning lights alerting the supervisor and a manual shut-down protocol. Monitoring machines using an effective IOT system to understand and interpret the data can lead to increased predictive maintenance that in turn optimises machine performance. "Using sensors to determine when machines need a service can prevent breakdowns and save on routine maintenance costs."

What should be emphasised is that to provide real value, your solution should be able to exchange data with your CRM, ERP and other enterprise systems. Only then will your IOT strategy be capable of triggering proper workflows.

Long-term considerations

Using data costs money and organisations all have data trapped in silos. Silos occur "whenever a data system is incompatible or not integrated with other data systems". By considering how an application will ultimately use data during its collection, you will be able to reduce the amount of data and the associated expenses of processing the data downstream. Wilder-James explains that enterprise applications are "written at one point in time, for a particular group in the company" and are "optimised for their main function". There are, however, still things you can do to facilitate data flow and alleviate integration issues.


The real power of IOT is its ability to evolve and grow with the often rapid changes in technology and the changing needs of the organisations it serves. These needs can include shifting customer demands (in a retail environment), the development of new products or services, increased responsive approaches to operations and maintenance, the incorporation of new systems and policies or real-time changes to production.

In deciding on the appropriate IOT business strategy, you need to carefully study your business model and analyse how to meet (and potentially exceed) the expectations of your customers. Transforming data into insights and ultimately greater revenue requires unlocking the silos and bringing together information from across the enterprise (while maintaining consistent IT security policies) so these remarkable tools can do their work. A transparent and flexible IOT strategy can enhance your business's digital transformation journey.

Ultimately, IOT is more than just connecting machines to the cloud. It's connecting your machines to your enterprise which, in turn, creates a central system of intelligence. But, to do this, you need to align your operations, your teams and your product offerings to give your business has the competitive advantage.

How does Polymorph help clients and partners unlock the value of IOT data?

We understand that extracting data from machines, storing it in the cloud and displaying it in an app is simply not enough. At Polymorph, we help our clients to unlock the value of their IOT data in three ways:

1. First, we gather, clean and store the data. This involves complexities such as connectivity, messaging protocols, cloud infrastructure, cloud storage, APIs and so forth. This is the focus for many companies at this stage of their IOT strategy; they are focusing on gathering the data and landing it in the cloud. Often, companies know that they should be doing this, but need help to do so. Using Polymorph's scalable IOT platform renders the process simple, cost-effective and quick to connect sensors and other IOT data sources to the cloud.

2. Our team members are experts in turning data into information through context-rich visualisations, apps and dashboards. The people that we're building it for, the decisions they need to make, and the business value it creates are important drivers for generating a return on investment from the data. Our team are experts in building data-user interfaces with the right context, turning data into information.

3. Finally, we make the information actionable by automating existing business processes, and feeding the information into those processes. We help our customers analyse and understand their business processes and can then implement those processes in our workflow engine. This allows actions and decisions to be taken on the information, transforming from data to information to actionable insights.

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