Smart Machines
It is a well-accepted fact that, thanks to M2M technology, very soon every machine on Earth will be able to talk about its health and performance. Machines will have the ability to communicate their information wherever, whenever and to whomever wants it. Every machine is going to be intelligent and smart, and in ideal situations, have a self-healing mechanism. Some simple examples would be automatically increasing room temperature in a data center, automatically and systematically notifying users and shutting down servers, and dispatching and scheduling transport assets based on telematics.
With these smart machines, it will become important for machine manufacturers to obtain the feedback from their machines after they are sold for the performance and accuracy of data and signals they produce. Further, manufacturers can no longer listen to just their own machines, but rather include feedback from machines made by other manufacturers, including the competition, to set the right benchmarks.
Social Media Enabled Collaboration
In today's world of massive communication and collaborative channels, like social media, mass reach, Internet spread, search engines, etc., nothing is hidden or a trade secret. It is apt for machine manufacturers to now learn from their customers, competitors, users, peers, agents, third parties and their own machines.
Social media and mass collaboration tools available today enable organizations to benefit from the collective intelligence of all such agencies, which would have been unthinkable a decade ago. A collaborative ecosystem is all about encouraging innovation, coordination of the supply chain and involvement of various stakeholders in the value creation process. Organizations that cultivate nimble, trust-based relationships with external collaborators are positioned to form vibrant business ecosystems that create value more effectively than traditional, closely-held, inward looking companies.
Collaboration with Customers and the Competition
A few years back, it might have been treated as blasphemy to ask companies to throw open the intricate details of their products to the general public. Not anymore. This is the era of prosumers, where consumers are co-designing and co-producing the products they would eventually consume. Progressive companies will bring customers into their business webs and give them lead roles in developing the next generation of products and services. This may mean adjusting business models and revamping internal processes to enable better collaboration with users.
Today, knowledge is being increasingly viewed as the product of networked people and organizations looking for new solutions to specific problems. In today's networked economy, proprietary knowledge has limited use. Companies that don't share knowledge are finding themselves isolated and ignored by networks that share, adopt and update knowledge to create value.
Is it risky to open up your equipment performance data to possible competitors? Yes, there is risk, but it is even riskier not to do so. The smartness is in creating an ecosystem that is stronger, loyal and more dynamic than that of your competitors. Very soon, competition is going to be between ecosystems, rather than between companies. When innovation is fast, fluid and distributed, it is important to build a loyal base of innovators. The bigger the ecosystem, the better it is because bigger ecosystems support more raw intelligence and more variety. The smart thing to do is to figure out what can be shared versus what can be termed as intellectual property that should not fall into the hands of the competition.
The first step in creating this ecosystem is to consider the equipment as part of the organization's extended enterprise asset landscape. Leverage the M2M communication framework and cloud-based social media channels to collect and collate the details of the equipment's health. In what is termed as crowdsourced-driven reliability, the people who are near the asset can sense the problem in advance and report to the maintenance department for a preventive action, thus preventing the asset's failure.
Going one step further, in these days of technological advancements, why rely only on people to do this? Why not machines themselves to do this reporting? That's where an M2M communication framework can help. Operational equipment generates lots of data. Only a small fraction of it gets processed for any useful purpose, and even then after a time lag. The rest of this data goes unused. The advent of machine to machine communication and social software provides companies with a way to document and leverage moments of innovation with relative ease. It provides a living repository of knowledge that grows along with the organization. The insights can be used to benefit the organization in various ways.
Governance Structure
Governance is one of the key challenges in such an open environment. How can organizations ensure that this proliferation of data is governed properly? Organizations need to figure out a way to manage the rather disorganized feeds from individual participants. They need to put in place a governance mechanism to decipher, scrutinize and integrate these individual contributions. A competitive differentiator for these competing ecosystems would be achieved in the way companies integrate, deliver and support their offerings with various complementary services.
Wither the organizational boundaries, for the ultimate winners will be those who accept and adopt the state of boundarylessness. They will focus their internal staff on value integration and value orchestration, while treating the world as their research and development (R&D) department.
Imagine this: For every unique product or homogenous group of products, an original equipment manufacturer (OEM) creates a Facebook©-like interface. Every time a sale happens, that customer gets added as a "friend" in this page. Furthermore, all vital performance statistics get fed into this page automatically, similar to chatter feeds in salesforce.com. All customers will be able to view the performance characteristics of their equipment as experienced by other customers. They can share best practices and optimal usage. The OEMs will have a first-hand view of after sales performance on all their products. The next version of the product would be the collective intelligence of all current customers. OEMs further look at rewarding customers for useful inputs in terms of extended warranty, free upgrade, etc.
This collaborative ecosystem helps in rapid diffusion of best practices, availability of just in time (JIT) expertise, faster positive feedback cycles, and increased horizontal and distributed models of research and innovation.
Conclusion
Social networking, the cloud and big data are all buzz words right now. But more than being just buzz words, they are now necessary ingredients in any organization's IT strategy. No part of business can afford to be disconnected from any of these and asset management is no exception. These technological advancements will go a long way in helping organizations meaningfully leverage the operational information emanating from production equipment.
Praveen Agrawal is a subject matter expert and recognized force in the industry in asset management, especially in Maximo, with knowledge levels spanning across functions and industries. He has global experience in executing various EAM and ERP projects for energy, utilities, manufacturing and telecommunications clients in various capacities. Praveen has been researching the EAM market for more than 15 years and is currently leading the Asset Management practice for Infosys.
Sajit Kumar C.N., is a Principal Consultant in Digital Enterprise Services for Infosys Limited. He has several years of diversified experience in the supply chain management and manufacturing domains. Prior to Infosys, he handled functional leadership roles at various IT products and services companies, including end-to-end conceptualization and development of the manufacturing module for a leading ERP product. A postgraduate in Industrial Management from the National Institute of Industrial Engineering, he is a Mechanical Engineer and holds multiple certifications, including CPIM (APICS), PMP (PMI), SAP SRM, etc.
