It’s no secret data and analytics are changing the world as we know it. Here are some ways it is having a profound impact on manufacturing, individually.
In manufacturing, even without modern data systems, you need to be aware of vast quantities of information. The reports include data about your personnel, the machines and equipment at your disposal, their status or condition, upcoming projects and deadlines — and even quality assurance concerns for the products or goods you are developing.
Luckily, big data technologies exist to make this a more manageable process, allowing you to collect, review, process and extract insights from all the information flowing in. On top of that, data solutions provide new opportunities — meaning new ideas — as well as a more detailed look at conventional information streams.
It’s pushing the rampant growth of big data technologies, as more and more companies implement it into their regular operations. That explains why Forrester predicts the global big data software market will be worth $31 billionOpens a new window by the end of the year, growing by 14 percent from last year.
As its adoption grows, here are some of the ways big data is proving to be a game-changer in the manufacturing industry.
1. Mass Personalization is now Viable
Consumers today demand a more personalized, relevant experience, which can be difficult to achieve with conventional manufacturing processes. Typically, you follow a one-size-fits-all approach and make minor edits or revisions over time to accommodate customer sentiment.
Big data turns all that on its head. You now have access to real-time insights on customer behavior, needs and demands, as well as their reactions or evolving preferences. In short, you can design and create goods to match precisely who your customers are and what they want. IT professionals can help when it comes to developing and crafting the kind of experiences mass customization requires.
Nike has a live-design experience for customers that uses this approach to allow for entirely custom shoes and accessories. It’s well beyond conceptual — it is now an innovative manufacturing process sweeping through the industry.
This benefit alone demonstrates how much of a game-changer big data solutions can be.
2. It Improves Operational Efficiency
Because you’re taking vast streams of data, combining relevant channels and then extracting valuable insights, you are effectively exploring all the information available to you. It then becomes possible to highlight bottlenecks, inconsistencies and even problems you may not have known about otherwise.
Even when looking at something like product quality, it provides more information you can then use to improve existing strategies or develop new ones. The real-time data coming in helps eliminate the risk too, because you can see exactly how specific changes influence customers and monitor their reactions.
It fosters a cyclical stream of improvement to not only produce better results, but also enhance existing operations.
3. It Provides Greater Visibility
Using big data and advanced analytics — especially in the supply chain — it becomes possible to measure and quantify just about every aspect of manufacturing. From product development and quality assurance to delivery and distribution, you suddenly have a multitude of details about performance, progress, inefficiencies, and problems.
You also have a more comprehensive oversight, which leads to improvements in efficiency and management. It is vital for streamlining workflows and processes, as well as building proper communication between you and your partners and vendors.
Transparency helps everyone adjust and respond to changes in the supply chain, including those on the manufacturing side that may have sweeping implications. If specific machinery is on the fritz and it’s going to delay shipments, everyone can plan accordingly.
Adversely, if consumer demand has spiked and you need to scale up the manufacture of something you offer, you can do it using a quantifiable system. Of course, on the IT side of things, that means funneling the right data to the proper departments and people.
4. It Lowers Warranty and Support Costs
On some level, you will always need to honor product and service warranties, especially as goods reach the end of their lifecycle. But poor manufacturing and design can lead to inordinately high levels of support and product recalls. Therefore, it’s vital to fine-tune manufacturing and mitigate the associated costs. McKinsey and Company highlights a case studyOpens a new window in pharmaceutical manufacturing that saw the use of big data to eliminate inefficiencies in vaccine production, which had a direct impact on inventory yield.
Big data and advanced analytics are useful for implementing a comprehensive and reliable quality assurance process. Using incoming data and performance metrics, you can determine whether you are meeting customer sentiment and quality perceptions. You can also learn things like the average lifecycle of a product, how goods hold up in varying conditions or environments and even identify design flaws to remedy in future iterations.
The real-time and ongoing process big data fosters mean consistent improvements and fine-tuning throughout the life of a product, which makes it even more possible to mitigate risks and costs. You can react to the market and customers more quickly, at a practically live level.
5. It Mitigates External RiskS
ome risks of doing business are out of your control. Supply chain dependencies, for instance, come with a degree of risk. If your materials provider suddenly hits a snag in production or the quality of the materials they are providing decreases, it is going to have a significant impact on your processes and output.
The biggest issue with these events is that you aren’t expecting them or may not have even planned accordingly. Yes, they can and do happen, and there’s no stopping them at times, but you can better adjust if you are up to date.
For example, maybe a severe weather pattern or materials shortage has affected the local markets. You can identify this early with analytics tools, and either adjust your processes to meet the changes or even source materials from elsewhere to make up for the losses.
The right planning and insights — which big data provides — can help mitigate risk on all fronts.