The Internet of Things (IoT) promises entirely new worlds of opportunity in many industries, but chief among them is the change that IoT and the machine-to-machine revolution is delivering in the manufacturing space.
The streamlined process, the end-to-end visibility, and the cost savings they deliver now and in the future mean that technology is just part of the story.
The real change is in the approach to process.
From hand-held devices to robotics and other innovations, the IoT advances deliver connectivity in an experiential framework that sets the customer at the center of the operations, but also connects an organization’s employees.
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Big Data, Big Opportunities
Companies are discovering that in an IoT environment with expanded boundaries, a new way of doing business has emerged that depends on the skill and training of those employees, and that’s where methodologies like Lean Six Sigma are making an efficiency difference.
The sheer volume of information that big data delivers to the operation, and that’s true in retail, health care, and other settings, makes it possible to see into process in ways that have never been achieved before.
That visibility extends into the manufacturing floor and the supply chain, and into the accounting and customer service spheres, where managers are discovering that the access to data is changing the workers as well as the work.
There’s so much more insight, but what’s the best way to leverage that?
The answer is simpler among decision-makers who are used to asking themselves that question, and working with their departmental counterparts to answer it in finance, marketing and the IT department.
IoT Bridges the Gap
But the IoT workplace draws all employees into the experience, and those in a leadership role need to ensure that every worker who can now see across the organization shares a methodology vision, too.
The main reason is because data is only useful to the degree that it’s reliable and actionable, and more of it is just volume unless it’s applied.
When data that’s increasingly derived from multiple sources and directions in real time delivers insights, then everything from manufacturing variation rates to logistics bottlenecks to driver safety and incentives becomes a part of delivering value on the basis of efficiency.
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Bringing Six Sigma Into Play
Employees who understand Six Sigma and similar quality and process frameworks are better equipped.
They’re not just navigating a transition to an IoT environment, because they’re active members of that environment and poised to act on improving it, rather than functioning as passive passengers who are just along for the ride, but who have no meaningful agency or capacity or investment in that IoT shift.
Six Sigma, for example, is project-based. Employees who engage in improvement projects have the sense of empowerment that the Six Sigma process supports, but that doesn’t mean that they just do without acting within the Six Sigma framework, and no matter how much they might want to jump right in and initiate change, that doesn’t happen until they’ve worked through a process that’s designed for successful outcomes.
Managers shouldn’t make the mistake of thinking that the immediacy of the IoT workplace and the speed of data are incompatible with the more methodical DMAIC cycle though.
The two are complementary and, when integrated properly, synergistic in the value creation they offer to both customers and the company.
When an employee is trained to think in terms of a roadmap that begins with definition, with understanding a challenge in the supply chain, or a barrier to creativity in corporate communications, that definition depends on quality data.
Where IoT is delivering constant data and more of it, it’s imperative that employees understand how to evaluate data sources to decide what and how to use it.
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The data shapes the definitions, and improvements are impossible unless those definitions are right. As variations of the old saying go, you can’t really get at the right answers unless you’re asking the right questions, and that’s why the IoT-driven data is so critical to defining a problem.
Because the workplace is so dependent on that data to move forward, it’s important to note that the IT department, from the beginning of any technology implementation, needs to plug into conversations about what kind of data really matter and how the organization’s people really use it to define things.
The definitions lead to meaningful measurement and the analysis of those measurements. Remember, Six Sigma methodologies have always been built on data, in fact, most criticisms have historically, and usually, questioned the emphasis on data at the expense of a holistic operational view.
But data is exactly what’s delivering the visibility to the IoT work environment and making that holistic view possible, so it’s only natural that the priorities of Six Sigma align with the overall organizational vision.
It’s when Six Sigma training enhances the ability of employees at all levels to act on the data that the real IoT transformation occurs.
If the methodology just stopped there, no amount of data would make for a more efficient operation, a better customer experience, and improved returns on investment, and that’s especially true when coupled with the lean approaches that are engaged in so many firms today.
The data analytics, and the streamlined IoT environment from which they are derived, are inseparable from the Six Sigma process improvements and the employee-driven projects that build upon them.
And if your business is at an early stage of determining the kind of technology infrastructure it will need to support operations in the IoT future, while deciding what people and processes will deliver its success.
Start with a Six Sigma framework from the beginning, and watch the data-driven transformation emerge, evolve and succeed in the competitive business climate that demands some real IoT decisions.