Is your organization part of the top 4%?

predictive analytics

It is not a secret that the amount of data generated in the last decade is big enough to equate multiple times the knowledge that humanity build out since its conception. A big chunk of it, is generated by sensors and pieces of equipment, and only a small proportion of that information is used by companies and corporations to learn about their past to understand the present, and finally predict the future.

All the ingredients are out there, and leveraging the power of Predictive Analytics and the necessary data, it is possible to predict with amazing accuracy when a machine will fail.

The good news is that this new reality is starting to be noticed by the decision makers and executives of companies around the globe.

Recently, Bain & Co, surveyed executives at more than 400 companies around the world (most with revenues over a billion dollars). Of those companies, only 4% are really good at analytics, improving their processes and products using actionable information extracted of their own data. The difference is noticeable:

  • Twice as likely to be in the top quartile of financial performance within their industries
  • Three times more likely to execute decisions as intended
  • Five times more likely to make decisions faster

So, if the benefits are that good, why are only 4% of the companies investing in good analytics?

We think the organizations are just starting to realize those benefits and starting to figure out how to get started.

There are companies that generate data and don’t have the knowledge to transform that into actionable predictions or companies that think their data is not complete enough or is “too messy” to extract good information from it. It is important for those organizations to understand that with relative small amounts of data, but with the correct statistical and visualizations tolls and techniques, companies can go from that 96% of companies that storage data and become part of that exclusive 4% of companies that make their data work for them.

Uptime Magazine – Can Your Machine Tell You When It Will Fail In The Future?

Predikto will be featured in Uptime Magazine  Feb 2014 issue with an article about Predictive Analytics called “Can Your Machine Tell You When It Will Fail In The Future?”.

The mission of Uptime Magazine is to make maintenance reliability professionals and asset managers safer and more successful by providing case studies, tutorials, practical tips, news, book reviews, and interactive content.

To view the article, click on the image below.


M2M Analytics Will Generate $14 Billion by 2018

Senior analyst, Aapo Markkanen, from ABI Research forecasts that the M2M analytics and big data industry will grow 53.1% over the next 5 years from US $1.9 billion in 2013 to US $14.3 billion in 2018.

The forecast includes revenue segmentation for the five components that together enable analytics to be used in M2M services:
1) Data integration
2) Data storage
3) Core analytics
4) Data presentation
5) Associated professional services

Predikto is uniquely positioned to make an impact in this transformational trend. Predikto is not a consulting company. Our solutions harness the power of Predictive Analytics to address operations challenges in asset intensive industries. We use our clients data and turn it into actionable insights to reduce asset failures, predict production yields, and improve operational performance. Our solutions enable clients to perform an action.

If it has sensors and it failed in the past, we can predict future failures!

Predictive Analytics is a proven technology for detecting and diagnosing emerging reliability problems far earlier than traditional methods. It is also a non intrusive method that should not be introduced to complete other predictive maintenance techniques and processes.

Some maintenance experts or operational executives believe it is difficult to predict failures in advance. They are correct that is is difficult, but Predikto makes the process very simple by performing a Proof of Concept on a few key assets without the need to install any software or build automated interfaces.

We love these challenges. We have a simple answer for skeptics: “If it has sensors and it has failed in the past, then we can predict when it will fail in the future”. It all starts by clients giving us some sample data and Predikto shows them what can be predicted in that particular case.

Reliability Analytics – Get Ready For It

Predikto spent two days at the SMRP show in Indianapolis last week. It was our first show and there were hundreds of representatives from many large organizations looking to learn about the latest technologies and process improvements to increase asset reliability and maintenance. It was very interesting to see Predictive Analytics or Reliability Analytics (as some people call it) as a trend that everyone was talking about and very few companies are actively doing. Some reliability experts where asking a lot of questions about Predictive Analytics and how it actually works, what type of predictions can be provided, and more importantly how to get started. Some clients were getting ready to hire IBM for large initiatives involving software and services acquisitions. Others had tried it inside SAP or other EAMs with limited success. Predikto recommends clients to start small with a targeted Proof of Concept and build from the early successes.

Reactive Maintenance and the Telephone Booth

I was walking through the streets of New York recently and ran into a public telephone booth. I was amazed at my reaction since phone booths are almost extinct. Earlier that day my family went to the Museum of Natural History to see dinasours up close and personal, and it’s amazing how all these different and interconnected animals are extinct as well. It got me thinking as to what practices in industrial manufacturing would become extinct in the next decade or two.

The fact that 50% of the experienced manufacturing workforce will be retiring in the next 5 to 10 years is adding a lot of pressure to organizations to improve automation and depend less on these seasoned “experts”.

So if improvements in technology and automation are key to ensuring US manufacturing continues to stay ahead of the pack, then what areas will become extinct? I believe organizations focused on reactive maintenance will eventually become extinct. These reactive firms who have not implemented best practices around preventative or predictive maintenance will be gobbled up by their better performing competitors, will be acquired by PE firms who will then trim the excess fat, or simply go out of business.

What do you think? What areas of manufacturing or maintenance do you think will become extinct in the next decade or two?

Interesting Facts About the Railroad Industry

There are 7 Class I railroads in the US: BNSF Railway, CSX Transportation, Grand Trunk Corporation, Kansas City Southern Railway, Norfolk Southern Combined Railroad Subsidiaries, Soo Line Corporation, and Union Pacific Railroad.

Unlike trucks, barges, and airlines in the U.S., freight railroads do not strain the public purse. Privately owned railroads have spent $525 billion since 1980 building, maintaining and growing their 140,000-mile rail network. That amount equals 40 cents of every revenue dollar. Even during the economic downturn, America’s freight railroads spent approximately $20 billion annually to build and maintain the most efficient rail system in the world. In 2013, that investment is expected to increase to an estimated $24.5 billion, helping to keep America competitive.

Average inflation-adjusted rail rates (as measured by revenue per ton-mile) are down 44 percent through 2012. That means the average rail shipper can move nearly twice as much freight for the same price it paid 30 years ago — saving consumers billions of dollars in shipping costs each year.

Railroads are much safer. From 1980-2012, the train accident rate was reduced by 80 percent and the employee injury and illness rate fell by 85 percent. 2012 was the safest year ever for railroads, breaking the safety records set in 2011.

Railroads are stronger financially. Return on investment, which had been falling for decades, rose to 4.4 percent in the 1980s, 7.0 percent in the 1990s, and 8.5 percent from 2000 to 2011. That’s important, because railroad earnings today lead to rail investments in new locomotives, tracks, bridges, and more so taxpayers don’t have to.