Big-data is about to have a big effect on a lot of industries. Will it impact the electronics supply chain anytime soon? Not likely. In fact, the supply chain seems to be choking on the data it already has. It's hardly ready to digest even more data in many different forms.
That's what Lora Cecere, founder of the research firm Supply Chain Insights, found in a recent survey of 53 IT and supply chain managers. That's a very small sample, but it does capture something that I've noticed lately. As a journalist, I'm covering big-data stories in all sorts of industries, but I haven't heard of any big-data projects in the supply chain. The survey found that supply chain managers recognize they should be doing more to take advantage of their data. A few respondents said they are launching big-data initiatives, but even they admit they cannot manage all that data.
Thirty-six percent of the respondents said they have cross-functional teams evaluating the potential of big-data for their supply chains. But the average respondent is dealing with four different enterprise resource planning systems. The 53 organizations had a total of 150 systems supporting their supply chains.
The data in at least some supply chains is growing to the point that companies should be able to crunch it for competitive advantage. Eight percent of respondents had at least one petabyte of data in a single database, and 47 percent expected to have a one-petabyte database within five years.
The respondents said they were best able to use data from several sources, many of them on the supply side, such as chain visibility, geolocation and mapping, and product traceability. In fact, the most common type of big-data initiative focused on supply chain visibility. But they also said they thought the biggest potential benefits could come from demand data, including mobile application, blog, voice, video, and social media data.
Most strikingly, there was a wide gulf -- for all kinds of data -- between how important respondents felt the data was and their ability to use it. Among respondents who reported having a big-data initiative, 95 percent said their most important data source was supply chain visibility, but only 58 percent said they had a good ability to take advantage of such data. That's a pretty big shortfall, and yet it turns into a gulf when looking at demand data sources. Seventy-four percent of respondents said user comments on ratings, reviews, and blogs were an important data source, but only 22 percent said their organization had a good ability to use that data. For data from social media, 68 percent said it was important, but only 17 percent said they could use it well.
"Clearly there is a lot of work to do for supply chain leaders who are already dealing with complex systems and now want to access new data types," Cecere wrote in a report on the survey.
Are you doing anything with big-data in your supply chain? How soon will supply chain managers be able to mine their data for competitive advantage?
Rosettanet was supposed to be an approach to solving, or at least addressing, the need for informational and transactional data through the electronics industry supply chain. I know it is insufficient to address provision of environmental data through the chain, but it wasn't mentioned in this study; are many companies actually implementing it? And are those implementing it using it to its capabilities?
The biggest challenge I see, as always, is having systems, processes, and people to deal with the data.
As much as I hate the idea of big data, I can see its value. But if you can't crunch the infomation you need, gathering it just creates more bottlenecks. This is going to be a tough one until systems and standards are in sync.
But if you can't crunch the infomation you need, gathering it just creates more bottlenecks.
@Barbara, I totally agree with you. Saving the big data as well as analyzing it will pose a big problem to the companies. But the companies who can master this will definitely get edge over other companies.
Using Big data , a central repository of all supply chain related data can be created by a central agency. This repository could contain the component information, distributor and retailer information, the various compliance related information , the real time supply and demand position of each and every component, price comparisons, lead times and all that kind of information could be stored.
But this kind of effort may be well managed bya consortium rather than the individual suppliers, buyers or manufactrurers
Agreed. Big data bigproblem. You need lot of man hours to mine the data, analyze it and then study the results and of course take necessary action. I guess companies need to have separate software teams to automate these things but then who will pay for this unless they see direct returns. May be for organizational development it will be good idea.
Data is always at the centre of the complete supply chain management. And to take better advantage of all the data available you need the right set of algorithms to help the users. There may more and more such applications evolve as different types business requirements grow in the future.
Agreed. One cannot run away from the problem. If the data is huge so let it be. Make use of the data, design something around it. Becuase supply chain data tells a lot of story.
Eight percent of respondents had at least one petabyte of data in a single database, and 47 percent expected to have a one-petabyte database within five years.
@Tam, No doubt demand for memory is increasing drastically. Recently Harvard researchers announced that they have cracked DNA based memory storage, packing a massive 700 terabytes of binary data into single gram. If we can commercialize this technology, then it would help us solve some of the challenges faced to store the big-data.
I think more challenging tasks still lie ahead - managing data across board big issue. Movement of data across - who's accessing what and what's being accessed? Nanotechnology would probably be taking care of more memory - nanoscaleability of memory device in particular very pertinent. Human genes?
@Wale, you are correct that storing, accessing and using the data is huge task. The current methods of storing the data is really inefficient and we need new methods to store data. Researchers are working on ways to store data on elementary particles but if we can tap biological material to store the data then we can probably store data cheaply.
@WB: Well, this is an additional perspective of the matter; as far as I know, it is a technology still really expensive a it is still strong trying to bring it on the ground for public use, respect to current legacy memories adopted. Maybe it will be good in the future, once again, not so easy (in my modest opinion), trying to define a credibile horizon for its definitely adoption.
The believe at many companies is that they need more data, about customers, the economy, suppliers, end markets, etc. Yet most haven't figured out what to do with the data they currently have.
The growing trend for that, i would say unstructured data - the adopting scheme for data distribution a major contributing factor. How many internet firms out there are handling unstructured data well? I dont know the impact of machine learning technique employing by Facebook, Amazon and Google etc in reducing the complexity. According to a report, put an estimate monthly internet data flow at near 21 exabytes of data, that's massive, i think. And we just have to prepare for more explosion of data few years time. A huge task?
Our company is not doing a lot on the big data front. I suppose it is a story of lots of data but not much information. Like many I suppose we need to do a much better job on this front.
Personally, I am feeling that on this matter, a strong point to address in the near future, will be about mobile data, in terms of how to store and provide secured features for allowing the online access.
@FlyingScot, which company do you work for? There are some big names that are working on smarter ways to analyze the data as the amount of data is growing per day and the cost associated with storing and analyzing is huge. But there are rich dividends in these fields.
Tam, good article. One solution that can help turn bigdata problems into big opportunities for any industryis HPCC Systems from LexisNexis which provides for an efficient low cost one-stop solution for BI and analytics needs. This open source enterprise-ready solution is comprised of a single platform that is easy to install, manage and code. Their built-in analytics libraries for Machine Learning and integration with other open source tools like Pentaho provide companies with an end to end solution for ETL,data mining and reporting. For more info visit: hpccsystems.com
Qualcomm has launched a big push to spread its cellular technology, and thus increase its royalty income, not to mention chip sales, beyond mobile phones.
You've heard the saying "the No. 1 supply chain risk is your people." That hasn't always been the case. But today's complex global supply chain requires a new type of multitalented employee. It's one who understands, finance, marketing, economics, is savvy with technology, graceful with relationships and can think analytically.
Where are these people? Are universities properly preparing the next generation supply chain professionals? How do train your existing workforce for these new, demanding positions?
Brian Fuller, editor-in-chief of EBN, will lead a 60-minute Avnet Velocity panel discussion that will ask and answer these and other questions swirling around today's supply-chain talent challenges.
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