At this point in the evolution of big data, most of us are familiar with its characteristics and potential to inform better decision-making. As far back as 2001, industry analyst Doug Laney listed the three Vs as integral to what made data ‘big’ – namely Volume, Velocity and Variety (see this recent Gartner report). In the intervening years, many others have attached additional characteristics, one of the most common being Value, to create the four Vs.
But as the size, speed and complexity of data has increased, it has often become harder and harder to derive value. As a result, the focus today in manufacturing and beyond has shifted to a fifth V – Visibility. With all the data accumulating in the cloud, in data centers and on the manufacturing floor, global visibility over what is useful and what is not has been obscured. Data in itself is worthless if it cannot be acted on, and the ability to do that can often be impeded by the sheer avalanche of information being collected. Visibility, data’s fifth element, will be the key to driving manufacturing intelligence and, ultimately, value for the bottom line.
Data Must be Visible to be Valuable
In reality, there is more than one type of data visibility across the manufacturing process. When thinking about data, we need to examine its flow. Acquisition takes place in analog measurements. Then, data will leave this point of origin, and become in motion. At this point it may or may not be analyzed in real time, providing instant visibility over critical operations. Situations where this may be advantageous are quality functions, where real-time information can be used to prevent a small, out-of-spec occurrence to becoming a large recall. Another example might be information about the temperature of an equipment component, which could be acted upon to prevent a motor from catching fire and leading to downtime.
Beyond real-time visibility, when data comes to rest on a server or at a workstation, deeper analysis can take place. It can be merged with historical data from the archives to examine trends over time. This information can then be linked into higher-level systems to help drive business decisions. It’s this type of high-level visibility – with data integrated across the enterprise – which will shape the future of manufacturing intelligence, and predictive intelligence. This has been the goal of Manufacturing Execution Systems (MES) since the mid-90s.
Greater Visibility Means better Responsiveness
Today’s global Manufacturing Operations Management solutions now have access to this level of data. Users can combine production efficiency with quality and visibility. The result is decreased time to production or time to global market, for new product introduction. Ultimately, this level of data visibility can help to deliver better manufacturing agility across the entire production process, beyond the plant floor to inventory, quality, maintenance and labor activities.
In the end, it all comes down to using the right data to make the right decisions. In an increasingly globalized market place, the differentiators that allow the best to stand out from the rest can be minute. Every possible advantage needs to be exploited. Providing the right information to people at the right time means better decisions get made about every aspect of manufacturing, including advanced planning, production capacity analysis, Work-in-Process (WIP), inventory turns and standard lead times. Though the individual gains made from big data visibility may be small, when added up they can be the difference between a business ready for the future, and one that’s stuck in the past.
If you liked this article, here are others you might also find interesting:
- Making Sense of Enterprise Manufacturing Intelligence
- Some Manufacturing Intelligence is Smarter than Others
- In Pursuit of the Transparent Manufacturing Plant
