Panel video replay title slide.JPGWelcome to Part 2 of our series on Big Data, the Internet of Things (IoT) and Machine to Machine (M2M) trends.  This blog series is based on my participation and discussions with a panel of leaders at the recent Manufacturing Forum (replay video)

As we discussed in Part 1 of this blog series, companies are generating a lot more data;  the most successful companies are effectively leveraging that information to drive competitive differentiation, disruptive innovation and profitable growth.    Best in class companies are embracing data-driven-decision-making.

Most of our day to day business processes are “reactive” instead of “proactive”.  Our businesses collect vast amounts of data.  Most of the time, it is too manual and time-consuming to sift through all of that data, looking into the past, drilling down to search for meaning.  Because anything meaningful that we do find, happened in the [distant] past, it is too late to take meaningful action.  I’ve heard many corporate leaders tell me that their organizations are “data rich, but information poor”.  This is caused by latency – a delay to access the data in a timeframe this is most useful;  latency is also negatively impacted by the time and effort it takes to adequately analyze and visualize data.  This latency leads companies to run by intuition instead of by the factual data of what is actually happening now.  Imagine if the gas gauge on your car gave you data that was a week old.   Now imagine that your job is to use your car in a race to beat your competitors who are using their own cars in the race.  Although you might not need to look at that gas gauge at every second, when you do look at it, you need real-time accurate data from which to base your decisions.  Without it, you would have to guess at your level of gas.  If your competitors had an accurate real-time gas gauge, then they would have a massive advantage over you.  Companies that wish to drive competitive advantage are shifting away from using intuition to make decisions;  they are moving toward using real-time data driven decision making.  To achieve this, companies are rethinking their approach to collecting, accessing, analyzing and visualizing data.

Best run businesses recognize that Big Data is not just a technology initiative,  but rather, a business initiative requiring technical know-how.   Furthermore, they recognize that traditional approaches, traditional IT systems, traditional business processes, and skill sets simply weren’t designed to cope with the challenges and opportunities provided by Big Data.  Best run companies are changing their organizational attitudes about using information.  They are re-evaluating their IT infrastructure, considering big data technologies like SAP Hana.  And they are enhancing their data analytical skills. According to this Harvard Business Review article, data scientist is the sexiest job of the 21st century.  Now tell me that’s not interesting.

But Big Data could also bring Big Opportunities for Manufacturers

Big Data has big impact on a number of industries, but especially on manufacturing.  A  McKinsey & Company’s public report on big data ranked manufacturing as one of the highest industries in terms of the amount of data managed and potential for additional insight within that data.

McKinsey - era of big data - sensors and alorithms .JPG

Tata - big data global trend study - ROI example.JPG

Here are a few of the value findings for manufacturers that are doing more with Big Data.  We’ll be discussing more on value in our next post.

10% estimated increase in revenue  (source: SAP Benchmarks)  

20-50% reduction in product development time (source:  Georgia Tech Big Data Research:  Manufacturing)

29% average ROI from Big Data projects in Manufacturing industry (source: Tata Consulting study, “Big Data Global Trends”)

Achieved IF more data could be accessed and analyzed

In summary…

Data-Driven Decision-Making is the employment of:

  • Data analysis techniques
  • Big data technologies
  • Visualization methods

Resulting in

A shift from using intuition to make decisions, to using data to drive greater growth, increased productivity, and sustained competitive advantages

Part 3 of this series will be posted soon and will focus further on Unlocking the Value from Big Data, IoT and M2M.  In the meantime, you can watch the presentation and panel discussion I had with leaders from Cisco, Pitney Bowes, LNS research and SAP – upon which this blog series is based  here

Panel video replay landing page.JPG

You might also like:

Business Trends driving CEOs (Part 1 of Big Data Series)

Empathy Lines the Path to Simple

A Time for Founders

Accelerating a Culture of Innovation

Panel: Big Data in Manufacturing – How Leading Companies Are Driving Competitive Advantage

About the Author

Patrick Maroney is part of the SAP Global Hana Platform Center of Excellence. In this role, he works closely with SAP customers to help understand the impacts of business trends on their processes and the use of technology in order to help architect business improvements. Patrick has a background in industrial engineering and business transformation consulting. Since 1992, Patrick has been working with the management teams of leading companies on improving their processes and leading business transformation initiatives.

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4 Comments

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  1. Gary Nelson

    This is outstanding information. Very insightful. In 2 years management is going to be asking CIOs everywhere why they
    haven’t upgraded to Hana.

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  2. Mitchell Clark

    Nice blog Patrick.  One question I often hear from customers is “how can I access and unlock the massive amounts of data stored in my SAP system to make better decisions faster”?  

    As you mentioned in your blog technologies like HANA can help answer this question.  To provide a real world example,  I recently built an ad-hoc query  to identify slow moving inventory that could be “taken off the books”.   A query was built using HANA and HANA Live that analyzed about 500,000 materials, 100+ million material movement documents, 150+ million demand elements and created a list of 20k materials that were potential candidates to be scrapped.   The query read real time data directly from the HANA database “underneath” the SAP ERP system. 

    It took about 30 minutes to create the query and 1 minute to execute it(the query was not optimized at all).   This is 31 minutes from the time the user posed the question to an answer being provided.    This is dramatically shorter that the time and effort required to create this type of query in a data warehouse type of environment. 

    This is a very specific use case ( not  necessarily as “glamorous” as IoT with sensor data), but exemplifies how tools like HANA can be brought to bear  to enable users to make better decisions faster.

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  3. Dan Somers

    We share your passion Patrick, especially in manufacturing:

    Our company, Warwick Analytics, has used the SAP HANA technology to build solutions for our customers that mine Big Data to automate root cause analysis.  For an example of one of our use cases, we mined IoT data to reduce the costs of poor quality 15% to 30%.   You can read more here –  http://www.warwickanalytics.com/how-motorola-slashed-copq-by-finding-a-needle-outside-the-haystack/

    Other use cases for resolving challenging problems quickly in automotive manufacturers and aerospace companies

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