At SAP, we believe the innovation is creating opportunities for businesses in four key areas?As your customers become more connected and mobile, you need to offer them the best experience wherever they are. You need to treat each of your customers as a “segment of one” - imagine a retailer can price every product to each customer individually in real time like the airlines, based on each customer’s preference and history, across any channel they are in. And you need to start treating your customers not as “consumers” but “co-innovators” who can bring the best and brightest ideas that you can turn into new products and servicesImagine if youwere able to offer your employees the right tools and insights to make the right call every time, have the right resources in the right place whenever the market changes, and grow and thrive when connecting to their customers and business partnersJust like the world we live in that is challenged with resource constraints, businesses must constantly find ways to optimize their resources. Increasingly, resources are not limited to physical assets like building and machines. The explosive growth of information is turning data into the next big resource. As they say “Data is the new Oil”. To best use your limited resources, companies must predict and respond to changes faster, in real time, and make immediate adjustments to optimize and maximize outcome. And optimizing resources is more about speed. In many cases, it opens up entirely new ways of doing business, especially in shifting products into services. Lastly, we are now living in a hyper-connected age. We all have been amazed by the new possibilities when people and businesses become connected. Imagine the possibilities when the world’s businesses are connected – we’ll be able to harness the insights and intelligence of entire communities to break down the barriers to collaboration and enable new processes that drive innovation and competitive advantage. I would guess that these opportunities and scenarios are resonating with all of you – we could all achieve all of this and more, if we weren’t struggling to address the complexity of the IT within our organisation, which has built up over the past decades.Believe me, you are not alone – complexity is one of the top challenges of our time and is really going to hamper the adoption of innovation if we don’t get it right. As an industry, we have all been guilty of adding to the this complexity, which has largely been driven by the underpinning technologies and their limitations.But the technology landscape has fundamentally changed in the last two years, so at SAP we are now uniquely placed to simplify the IT stack and accelerate innovation.
NBA statistics, powered by SAPHANA: http://nba.com/statsThe NFL fantasy football information, powered by SAP Analytics -- For more information, please see this link: http://www.sap.com/corporate-en/news.epx?PressID=20323Also San Francisco 49ers scounting application: And NBA.com/statsObjectivesGrow the game of basketball on a global basis – 215 countriesDrive greater engagement among more than 380 million fansMaximize the use of more than 65 years of statistical dataUp to 20,000Concurrent queries of the statistics database2xMore time spent by fans on NBA website5 minutesAfter each game the stats website is updated
Washing machines already recording what's going on... just now starting to get exposed...
http://www.youtube.com/watch?v=ei_qgUYkq9UCyberfleetPirelli> 40 billionevents per year analyzedUp to 20 % extended tire lifespanUp to 3% reduction fuel& tire costsScenario: Record, transmit and analyze tire information in real time using SAP HANA predictive analytics and geospatial functions Business Challenges/ ObjectivesEnable fleet manager to deliver new services that monitor tire usage and predict maintenance Deliver timely insight each month on cost / profitability analysis, sales & distribution, and supply chain managementTechnical ChallengesProcess and analyze large volume of data real time: 40 billion events per year (600 fleets per system,1.000 assets (trucks etc.) per fleet,6 active tires / asset,1 message / tire / every 2min, 16 h a day,6 days a week)Analyze tire data (pressure, temperature) from sensors, GPS data, and customer records in real-time to predict diagnostic / maintenance workBenefitsIncreased competitiveness and innovation with new technology Increased customer satisfaction with proactive maintenance of tiresLower running costs by cutting fuel consumption Extended the tire lifespan Improved safetyCompany ProfileFounded in 1872, Pirelli is the fifth biggest tire maker in the world in terms of sales. Present in over 160 countries, today it has 22 tire production facilities located on four continents and counts about 37,000 employees. Pirelli estimates its value at €2.27 billion.Pirelli has been an SAP customer for a long time, running several solutions in the SAP Business Suite, including ERP, CRM and SRM to name a few. With SAP HANA, Pirelli is looking to deliver real-time analytics to provide insight on cost/profitability analysis, sales & distribution, and supply chain management.In addition, Pirelli is interested in working with SAP as a valued partner to develop innovative solutions. In particular, Pirelli is developing a new services, Web-based application that runs on SAP HANA to provide fleet managers of vehicles the ability to gain new insight on the use of tires, predict maintenance, and increase customer satisfaction.Inside of each tire is a sensor that collects data relating to pressure, temperature and identification which is can be transmitted to the driver, fleet manager or dealer, allowing them to plan diagnostic and maintenance work, which guarantees the best possible safety standards for every vehicle in the fleet”With SAP HANA, Pirelli can capture and store and analyze data from multiple fleets to discover new insights, such as correlating street conditions, climate and local practices, and using that insight to improve product quality and performance”1. Key SAP HANA featuresPredictive AnalyticsGeospatial SupportIntegrated Application Services (XS) / Mobile ApplicationsReal-Time Analytics for SAP Business Suite reporting (cost/profitability analysis, sales & distribution, supply chain)2. Technical KPI’sFuel consumption, tire lifespan, early warnings:Fast DeflationLow PressureService IntervalTemperature MonitoringEfficiency Level 3. Co-Innovation with SAP 3 month of development4. PartnersSpecTec (http://www.spectec.net)
http://www.reinhardkaufmann.de/PDF%20Files/ESA/Telemetry%20Brochure.pdfTrent 800 is the market leading engine on the Boeing 777 with a 41 per cent shareOverviewEngine detailsThere are over 500 Trent 800 engines on 220 aircraft operating in service todayOver 21 million hours and 4 million cycles of Trent 800 operation achieved by December 2012 Lowest weight, greater payload, greater revenue-earning capabilityThrust available from 75,000lb to 95,000lb from a single bill of materialCompetitive fuel burnLow noiseLowest emissionsModular build ensures ease of maintenanceReliable and predictable throughout its lifeThe three shaft architecture allows convenient transportationA Trent 800 powered Boeing 777 takes off or lands every 96 secondsThe Trent 800 entered service in April 1996. Built on the solid foundation of Trent 700 (entered service in March 1995) experience, the Trent 800 was certified ahead of schedule at 90,000 lb thrust, exceeding its original target of 84,000lb.The Trent 800 rapidly established a reputation for industry-leading reliability and the capability of the original design has been demonstrated by continuing thrust growth. Today the Trent 800 is available from 75,000 to 95,000lb thrust with a common engine standard, the widest range of any engine in its class.The Trent 800 is the power plant of choice for the 777, having secured orders for 40 per cent of the available market.
SAP HANA reduces analytic run-time from four days to 35 seconds!http://www.warwickanalytics.com/warwick-analytics-talk-advanced-analytics-in-manufacturing-digital/http://www.manufacturingdigital.com/magazines/14439Manufacturing IT: “Advanced analytics goes beyond conventional statistics and statistical process control. It doesn’t just capture the trends towards out of tolerance, but looks at “in-tolerance” failures, i.e. where issues have developed in spite of all the controls being within tolerance to identify the root cause. More importantly, the key advancement of advanced analytics is that the data can be disparate, incomplete and “dirty” (as is often the case on the shop floor in manufacturing) and it identifies and recommends resolutions to issues without the need for hypotheses. Normally an engineer would need to act as a data scientist, setting up hypotheses and using sophisticated statistical tools such as multivariate analysis or logistic regression to try and solve such issues. For multivariate problems with dirty and/or incomplete data, this might take months if at all solvable. Much of the time, engineers have ‘workaround’ solutions where they don’t understand the root cause or know if they are overcompensating or even causing an issue elsewhere such as clash tolerances. “Benefits from manufacturers already using advanced analytics software such as from Warwick Analytics show up to a 75% reduction in the cost of fixing yield issues, and a 50% reduction in warranty resolution lead time”The BenefitsIt can act as an early warning and prevention system, stopping defective products from being produced and predicting when and how products in the field - such as aircraft or vehicles - require maintaining.The output from the analysis will be markers that identify either an exact root cause of failure or a region with a high probability of failure. From identifying these fault regions engineers can work out corrective actions such as remanufacture, redesigning the product or to specify precisely the products in the field which require corrective action, and the lowest fix, without having to recall the entire fleet or batch, or implement an expensive workaround. Advanced analytics can also improve the availability and safety of …etc…Notably, the technology now within Warwick Analytics was applied at Motorola, the home of six sigma, to support their quality processes. It was used to eliminate two of their most prominent quality issues for a particular mobile phone model which were No Fault Found issues related to audio and battery and were costing Motorola a significant amount in terms of returns, replacements and reputation - the typical costs associated with COPQ.The results of the analysis picked out the key parameters — all within tolerance — that were contriving to cause the root cause of the issue. Furthermore the “fault region” was also quantified, meaning that it was possible for the manufacturing engineers to easily identify and predict when the failure would occur again. The faults could therefore be swiftly and almost entirely eliminated by Motorola adjusting its Statistical Process Control to obviate the problem so that no latently faulty phones passed the EOL testing. The model of phones was also redesigned in the next generation to improve the yield inside the factory. In conclusion, as a result of using the advanced analytics, the NFF issues were no longer in their top 50 warranty failures.
Warwick analyticsMobile phone factory, no fault foundCase Study - MotorolaUK: +44 (0)20 7060 6990US: +1 (408) 641-3148E: firstname.lastname@example.org W: www.warwickanalytics.comMotorola is not only one of the first and largest mobile telecoms manufacturers, it is also the originator ofSix Sigma - the quality standard strived for by the majority of engineers worldwide.Whilst they still widely implement Six Sigma techniques across their factories and processes, Motorola recently went one step further and utilised new technology developed by the academic co-founder of Warwick Analytics to solve a No Fault Found (NFF) issue and significantly reduce their Cost of Poor Quality (COPQ).The issueTwo of the most prominent quality issues for a particular Motorola mobile phone model were NFF issues related to audio and battery. These issues were costing them a significant amount in terms of returns, replacements and reputation –the typical costs associated with COPQ.The processData supplied by Motorola was analysed using the technology now known as Root Cause Analysis Solver Engine (RCASE), which form the core algorithms within SigmaGuardian, Warwick Analytics’ Early Warning and Prevention system.The data provided were warranty data that highlighted NFF issues and also End of Line (“EOL”) testing process data consisting of 170 parameters. Although reasonably comprehensive, the warranty data was incomplete and “dirty” thus making any statistical approach to resolving the root cause extremely challenging. Note that all of the 170 testing parameters were within tolerance, meaning that it was not possible to identify the root cause of the problem from this data alone.However, as RCASE is based on information theory and is ‘non-statistical’, it takes whatever data is available, whether dirty or incomplete. It does not rely on assumptions or setting up complex multivariate analyses. Even if the key parameters causing the issue are not present in the dataset, it will never give an incorrect answer, and it will still narrow the search space and advise where to look next. This is a different approach to statistical theories which try to find a best fit and can be skewed on incomplete datasets.The solutionThe results of the analysis picked out the key parameters which, albeit all individually within tolerance, were in combination contriving to cause the root cause of the issue. Furthermore, the ‘fault region’ was also quantified, meaning that it was possible for the manufacturing engineers to easily identify and predict when the failure would occur again. The faults could therefore be swiftly almost entirely eliminated by Motorola adjusting its Statistical Process Control to obviate the problem so that no latently faulty phones passed the EOL testing. The model of phones was also redesigned in the next generation to improve the yield inside the factory.In conclusion, as a result of using RCASE, the NFF issues which were the top 2 warranty failures were nolonger in the top 50 warranty failures.This paper introduces a methodology for functional capability analysis and optimal process adjustment for products with failures that occur when design parameters and process variables are within tolerance limits (in-specs). The proposed methodology defines a multivariate functional capability space (FC-Space) using a mathematical morphology operation, the Minkowski sum, in order to represent a unified model with (i) multidimensional design tolerance space; (ii) in-specs failure region(s); and, (iii) non-parametric, multivariate process measurements represented as Kernel Density Estimates (KDEs). The defined FC-Space allows the determination of a desired process fallout rate in the case of products with field failures that occur within design tolerances (in-specs). The outlined process adjustment approach identifies the optimum position of the process mean in order to minimize the overlap between the KDEs and in-specs failure regions, i. e., achieve the minimum possible process fallout rate for current process variation. The FC-Space-based process adjustment methodology is illustrated using a case study from the electronics industry where the in-specs failure region is identified based on warranty information analysis.
“non statistical based on information theory”COPQ is high typically because root causes of faults are hard to identify, as well as the competitive pressureto launch ever more complex, innovative products. The state of the art of resolving faults requires many disciplines: deep engineering knowledge, structured problem-solving approach, statistical tools, IT and data science. Many organisations, even when they have all these skills available, struggle to deploy them in the right quantities when and where they need it to solve big issues and clear backlogs of lesser ones. Most of these issues are multi-million dollar problems, and time is money. Many times, a workaround is implemented and there is no 100% certainty that the fault will not reoccur. Unless the problem is fully understood and holistically considered (including throughout the supply chain), clash tolerances can mean that a tweak here to repair one issue could mean an issue occurring somewhere else.On top of this, some of the most challenging type of issues to resolve are No Fault Found problems, where the symptoms are transient and/or intermittent. These are particularly difficult to diagnose and resolve and usually require a lot of trial and error and workaround solutions without really addressing let alone understanding the real root cause.All of these challenges are further amplified by the challenges of managing and analysing the data required which are often dirty and/or incomplete and/or unstructured, for example manual text. Typicallythere is either too little or too much i.e. ‘big data’ which can be worse.It is possible to identify these regions by exhaustive search or manual methods, although the numberof possible regions is n! (factorial) because any number of of the parameters in combination could be causing the issue (i.e. the fault region can be multidimensional).The kind of technology as exemplified within SigmaGuardian has been specifically developed to identify these fault regions from in-tolerance failures as rapidly as possible and before they become statistically significant which by definition means before statistics can detect them (and before they become expensive or catastrophic). More below.
http://www.futuregov.asia/articles/2014/mar/17/why-australian-state-fire-rescue-chose-sap-emergen/Sap business suite on hanaPUBLIC SAFETYWHY AUSTRALIAN STATE FIRE & RESCUE CHOSE SAP FOR EMERGENCY MANAGEMENT AND EARLY-WARNING SYSTEMBy Kelly Ng | 17 March 2014 | Views: 1108Australia’s Fire & Rescue New South Wales (NSW) has rolled out a suite of business applications that will support network-wide move toward real-time reporting and access to information across the entire emergency services network in the Australian state of 7.2 million people.PHOTOSView photosRELATED ARTICLESAustralian State launches GIS-based emergency response systemAustralian State launches GIS-based stock route management systemAustralian university rolls out new learning management systemRELATED CATEGORIESPUBLIC SAFETYFROM THIS SECTIONNEWSFire & Rescue NSW was looking for ways to improve control during the fire season, predict fires and other natural disasters before they happen, as well as effectively manage resources and establish early-warning systems.The implementation of SAP Business Suite powered by SAP HANA has given the Agency ready access to deep and accurate information so that enables it to make critical decisions quickly, as well as monitor and manage its entire network more effectively.“The SAP software implementation will help us save lives,” said Fire & Rescue NSW CIO Richard Host. “It knows everything about our assets and our people, including their training history, with up to 30 years of data.”“We will also see more efficient collaboration across the three major state emergency service agencies — NSW Fire & Rescue, NSW State Emergency Service and NSW Rural Fire Service. The agencies now use a single instance of SAP Business Suite powered by SAP HANA as their source of information,” Host added.SAP and Fire & Rescue NSW have enjoyed a longstanding relationship and together have transformed the agency’s business processes and systems.SAP Business Suite, which now runs on the in-memory platform SAP HANA, offers a complete solution for Fire & Rescue NSW and enables the broader emergency services network in NSW to collaborate more effectively. Delivering improvements to internal processes, using SAP also allows each agency to manage its business operations more effectively.With SAP HANA, Fire & Rescue NSW is looking to the future with an enterprise asset management program to help the Emergency Services Agencies better manage their vast firefighting and rescue asset base.The platform is envisioned to also support the agency’s “Project Minder,” a system designed to head off disasters across the state by analysing real-time data and enabling predictions up to almost a week in advance, as well as to recommend resource deployment in a timely and accurate manner.“Fire & Rescue NSW have delivered an exceptional implementation,” said Andrew Barkla, President and Managing Director, SAP Australia & New Zealand. “We have laid the foundations for continuous innovation that will improve not only the state’s emergency response, but emergency prevention. This maps directly to SAP’s mission of helping the world run better and improving people’s lives.”
Improved churn model by 47%
Or retailer…or bank…
Driving business innovation through big data analytics
Timo Elliott, SAP Innovation Evangelist, March 2014
Driving Business Innovation Through
Big Data Analytics
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