Advanced Industrial Services: How Are Big Data and Analytics Shifting Gears?
Services, when defined in conventional and generic terms, tend to revolve around product-oriented or result-oriented approaches. These services possess the potential to be advanced by the product/service provider on the basis of the customary norms established by the belonging industry. After-sales service is one such example where conventional services are advanced or extended for greater customer satisfaction and increased brand value.
Advanced industrial services in the current scenario, however, are not what we understand from the example above. These are achieved by the implementation of high-profile digital technologies and incorporation of the data, thus generated, to produce unprecedented productive results.
Before we move on to understand how Big Data & Analytics is taking the front seat in transforming advanced industrial services in the manufacturing sector, let’s understand the complete scope of such services.
Advanced Industrial Services: Scope or Nope?
As Bain and Co. call it, Advanced Industrial Services can be pretty much summed up as digital disruption of services.
Unlike traditional services, advanced services focus more on value creation processes, which may not be attained through preliminary and standardized solutions and may require manufacturers to go several steps further.
Reducing costs, saving time, simplifying data mining, integrating functional processes, and eliminating redundant and obsolete procedures are few of the objectives that remain pivotal to the advanced services value chain. The ball here is in the manufacturer’s court as they play a quintessential role in assimilating the right digital resources at the enterprise level and aligning them in the direction of the target.
Primary Service Offerings That Are Booming Thanks To Big Data & Analytics
It would be the understatement of the year if we call Big Data Analytics in Manufacturing a thriving industry. According to recent reports, the industry is valued at over $904 million, and that’s before it has even reached its full potential or recognition. Companies and manufacturers looking to gain an edge are using digital technologies in three primary service offerings.
Let’s explore how and what constitutes the world of difference that it makes.
Predictive maintenance is a determinative technique to find out whether the machinery parts or equipment which are currently in-service, are adequately functional. It also makes educated guesses on the conditions of machinery to estimate maintenance and servicing needs, costs, and timelines. That's where the term “predictive” comes from. Being a preventive measure, predictive maintenance maximizes efficiency, minimizes downtimes, and therefore, losses.
Big data analytics can enhance the way predictive maintenance performs by many folds. In a capsule, big data technologies integrate with predictive maintenance to accelerate advanced services development in the following ways:
- Increases the capacitative volumes of the database systems, more than the conventional ones.
- Allows the integration and unification of the data streams and assists predictive analytics in streamlining the outcomes of the services.
- Provides real-time support for the analysis of a bulk of data points (sometimes up to millions) per second. This facilitates instant reports of the assets and that further helps to avoid untimely mishaps or downtime in the manufacturing or even unplanned equipment failures.
- Capitalizes on the 4 V’s; Volume, variety, velocity, and veracity.
- Provides means to the predictive maintenance methods to find out errors and other faults in the equipment.
Unlike its predictive counterpart, remote maintenance is more customer-oriented and has little to do with manufacturing. It centers itself in the after-sales lot, the part of the advanced service that begins once the customer has sealed the deal. It involves the comprehensive operative, analytical, and monitoring services that your client needs as a part of IT solutions and providers offer from their remote workstations.
Since remote maintenance essentially draws its efficiency from advanced tools, technologies, and analytics, big data exploits the exponential scope in this field in the following ways:
- Maintenance data is collected into the ERPs to optimize planning and operations.
- Performance data extracted from the equipment signals are processed and analyzed to detect any deviations from target performance and productivity, as well as optimize the use of consumables. Corrective measures can be thus taken to save costs, time, and resources.
- Big data is logically warehoused and with the help of advanced analytical tools, remote maintenance is empowered with better decision making.
According to a Service Circle Survey by Bain and Co., a greater share of respondents in the industry plan on expanding advanced industrial services in the remote monitoring and maintenance area than in predictive maintenance. The reason is simple; remote maintenance and its benefits are transparent to customers, and they are more likely to pay for this advancement whereas predictive maintenance happens behind the scenes.
Operational efficiency is nothing but optimization -- achieving the best quality, in record time, with optimal investments in the right resources and an assuredly profitable ROI.
Big data analytics multiplies the accuracy and precision in corrective calculations which form the basis of newer business strategies and operations. Another evolutionary power that big data and analytics hands over to advanced services is the analysis of customer behavior; it practically tells you the buying and ownership tendencies of your target groups which enables service providers to adapt and customize.
Finally, you cannot possibly imagine operational efficiency without going digital and social, can you? The amounts of forecasting that the collection of data from social media and the world wide web and subsequent analysis can do is incredibly rewarding to service providers.
What Lies In The Future?
There’s no limit to the extent of growth that can be attained in the service sector with big data. As long as Big Data continues to empower and industrial services, greater advancements will be a given.
However, it’s important to note that advanced services and big data incorporation are all about a two-way approach. A smooth liaison is essential between the manufacturer and customer, in order to facilitate the former to enhance functional values of the processes by incorporating a more goal-oriented set of operations.
Unless your strategies and service contracts are convincing enough to please your customer and generate a win-win situation, the balance between investments and profitability would be hard to achieve. Do you have any questions? Feel free share your doublt with us.