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Navigating the Supply Chain Management Fault Line - by @lcecere
"Fire the narcissistic supply chain leaders that believe that they have the answers. We don’t have the answers. We have historical practices, not best practices. Stalled progress on metrics: 90% of companies find themselves stuck on key supply chain metrics (cost, inventory, growth, ROIC)."
big  data  supply  chains  digital  chain  3pls  artificial  intelligence  business  process  outsourcing  cognitive  computing  innovation 
15 days ago by jonerp
Singapore CIOs believe machine learning can improve speed, security ops
"The CIOs, though, recognised the impact of machine learning on business automation, with 87 percent in Singapore noting this could improve their company's profitability and top-line growth over the next three years.

Another 41 percent said decision automation, enabled by machine learning, would better facilitate the development of new products and services for their organisation."
big  data  analytics 
23 days ago by jonerp
Blockchain: Reflections on a Webinar - by @lcecere
" Blockchain is an immutable ledger. On the webinar, Juan Ruiz from IBM used an analogy that I loved. He shared the story from his boss. She describes immutable as completing a crossword puzzle with an ink pen versus a pencil. When you use a pencil on a crossword puzzle, you can erase the entries. However, in the use of the pen, the first entries stay and are then crossed through. This is a great analogy to understand “immutable” as it pertains to blockchain."
big  data  supply  chains  blockchain  chain  excellence  innovation 
23 days ago by jonerp
Monetizing Big Data in Next-Generation Mobility - by @esimoudis
"The value of big data and AI for perception, localization, and planning, as well as map creation and other aspects of autonomous movement have already been documented and apply in all of the six use cases presented above. Obviously the performance of autonomous vehicles improves as more data is collected from test and production vehicles because such data leads to the continuous improvement of the perception, localization, and planning modules."
autotech  big  data  ai  automotive  value  chain  autonomous  vehicles  monetization  next-generation  mobility 
9 weeks ago by jonerp
Dissecting the Headwinds and Tailwinds of Digital Transformation - by @lcecere
"At the Supply Chain Insights Global Summit last week Gita Gopinath, a Harvard University economist, forecasted worldwide global growth at 3.6%, but only 1.9% for the more advanced economies in Europe and North America. In contrast, she forecasts growth rates in the emerging economies of Europe and Asia at 4.8%. For the global multinational, powering global growth in China and India is tougher, and with greater intellectual property risk, than driving a digital transformation in North America and Europe."
big  data  supply  chains  demand  digital  blockchain  transformation  growth  headwinds  internet  of  things  new  business  models  chain  tailwinds 
september 2017 by jonerp
Mining Supply Chain Data for Insights - by @lcecere
"So if a technology vendor in supply chain planning promises improvements in costs and inventory, be wary. Pour the coffee strong. However, do not throw the baby out with the bath water. Planning can drive results if the organization has the right DNA. Focus on defining supply chain excellence and the appropriate use of the technologies. Test and verify results and build planning into data-driven processes. Do not treat supply chain planning as a typical technology project focused on implementation. Instead, refine the data model and test outcomes."
big  data  supply  chains  demand  driven  market-driven  chain  blockchain  cognitive  computing  sensing  efficient  frontier  metrics  that  matter  robotics 
september 2017 by jonerp
Design Thinking: Future-proof Yourself from AI
"While there is a high probability that machine learning and artificial intelligence will play an important role in whatever job you hold in the future, there is one way to “future-proof” your career…embrace the power of design thinking."
big  data  ai  artificial  intelligence  design  thinking  machine  learning 
september 2017 by jonerp
Cognitive Computing: Getting Clear on Definitions - by @lcecere #scm
"A hype cycle starts with a technology trigger. In the case of cognitive computing, the trigger is the use of sensor technologies along with in-memory processing to sense, learn and act. We are witnessing the evolution of analytics for pattern recognition, and unstructured text mining along with the redefinition of architectures to enable streaming data and real-time process innovation. The work by Google on manless vehicles or the department of defense’s work on ‘bad guy detection’ spawned early innovation. Despite the powerful and brilliant, IBM Watson marketing machine, realize that it is still early. Only 7% of manufacturers are experimenting with cognitive computing."
big  data  supply  chains  demand  driven  cognitive  computing  models  machine  learning  ontologies  chain  unstructured 
august 2017 by jonerp
A New Red Wagon? - by @lcecere #scm
"Today’s organization is handcuffed by a forced march for IT standardization and process uniformity. Each project requires a defined ROI. It is ludicrous to ask for a ROI on the unknown. As a result, process innovation is difficult. Break the cycle and invest in small projects with an unknown ROI. Build a governance process, like product stage gates, and focus on process innovation. Innovate at the edge and evolve at the core. Evolve both together. (Note: This is very different than the espoused bimodal evolutionary path.)"
big  data  supply  chains  global  chain  insights  chemical  industry  new  technologies  process  innovation  red  wagon 
july 2017 by jonerp
Analysis Of The Next-Generation Mobility Value Chain - by @esimoudis
"In the previous post I described a new value chain that will connect companies providing on-demand mobility and three emerging models for the realization of this value chain. This value chain is the result of the consumer shift from a car ownership-centric transportation model to a hybrid model that blends car ownership with mobility services, and the stated intent by the providers of certain of these services to adopt of Autonomous Connected Electrified (ACE) vehicles."
autotech  big  data  automotive  innovation  driverless  vehicles  next-generation  mobility  on-demand  value  chain 
july 2017 by jonerp
IBM Ends Hadoop Distribution, Hortonworks Expands Hybrid Open Source - by @merv
"IBM has followed Intel and EMC/Pivotal in abandoning efforts to make a business of Hadoop distributions, and followed Microsoft in making Hortonworks its supplying partner."
apache  atlas  hadoop  hive  impala  big  data  cloudera  gartner  hortonworks  ibm  biginsights  microsoft 
june 2017 by jonerp
SapphireNow – is SAP poised to lead the industry again? - by @dealarchitect
"I also did not like Plattner announcing in his keynote S/4 is “basically done” or the fact that he said some bloggers had confirmed to him he was correct. Not this blogger – to me S/4 is where R/3 was in 1995. As we saw over the next decade, SAP (and other ERP) vendors had to expand functionality in CRM, SCM, EAM, BI and many other categories. SAP also had to launch a wide range of IS, industry solutions."
business  featured  posts  technology  software  analytics  big  data  cloud  computing  enterprise  (ibm  microsoft  oracle  saas  sap 
may 2017 by jonerp
That giant sucking sound? Hadoop moving into the cloud - by @monkchips
"Even in the cloud though it promises elastic scalability, capacity planning is an issue – what happens when your Hadoop cluster grows out of the sizing you have set up on AWS Cloud? Hadoop and associated tooling carries a fairly significant management overhead. While the distribution players can mitigate these issues to some extent, the alternative is managed serviced from AWS, Azure and Google Cloud Platform (GCP."
featured  posts  technology  software  aws  azure  big  data  bigquery  bigtable  gcp  google  hadoop  microsoft 
may 2017 by jonerp
A new value chain for next-generation mobility - by @esimoudis
"In my book, The Big Data Opportunity in Our Driverless Future, I make two arguments: 1) that societal and urban challenges are accelerating the adoption of on-demand mobility, and 2) technology advances, including big data and machine intelligence, are making Autonomous Connected and Electrified (ACE) vehicles a reality. ACE vehicles and on-demand mobility will cause three major shifts that can lead to the disruption of the automotive and transportation industries: a consumer shift, an automotive industry shift, and a mobility services shift."
autotech  big  data  automotive  innovation  value  chain  driverless  vehicles  next-generation  mobility  on-demand 
april 2017 by jonerp
Microsoft Puts AI Where the Data Is
While the machine learning and artificial intelligence landscape is far more complicated than the database market, if Microsoft can turn SQL Server into a platform where enterprises can work with machine learning and AI from the comfort of their own database systems, where they have familiar controls and development tools, then AI and ML may truly find a home in tomorrow’s enterprise.
technology  top  stories  artificial  intelligence  big  data  deep  learning  documentdb  hadoop  machine  microsoft  r  server 
april 2017 by jonerp
Data Transformation is the New Digital Transformation - by @monkchips
"Bardin said key to hiring and retention was keeping the challenges interesting, so the practitioners had a stake in success and a pipeline of interesting challenges to take on, that matched their skillsets. To some readers many of these ideas probably sound like business as usual, but they come across as very refreshing from a major French bank, and let’s face it, most of us look more like that than a true Cloud Native. Bardin is basically leading a best practices lab for data science. If you get a chance to see him talk I highly recommend it."
uncategorized  big  data  science  hadoop  python  spark  ifrs 
april 2017 by jonerp
Research Summary: Artificial Intelligence Delivers Mass Personalization In Commerce - by @rwang0
"Lack of relevance leads to lack of engagement. Contextual relevancy can be correlated to an immediate effect on the top line. Constellation estimates that lack of content relevancy often results in 83 percent lower response rates in the average marketing campaign. Conversely, personalized contextual relevancy by time of day, geo-spatial location, weather, and identity improves commerce conversions between two to three times over normal non-personalized campaigns."
2017  ai  anticipatory  analytics  apps  strategy  artificial  intelligence  augmented  humanity  b2b  e-commerce  b2c  big  ideas  bigdata  business  transformation  cadence 
april 2017 by jonerp
Hadoop FAQs – April Webinar Q&A - by @merv
"What do you mean by calling Spark part of the Hadoop stack? Previously you indicated that they were independent, and you made it sound as though organizations were simply adding Spark to their offerings.
Spark is completely independent from Hadoop, but it was created to run in the Hadoop environment (among others). This made it relatively easy for Hadoop distributors to ship Spark as part an aggregate offering. When we describe Spark as part of the Hadoop stack, we’re referring to commercially available Hadoop distributions."
apache  flume  hadoop  hbase  mapreduce  spark  sqoop  big  data  cloud  integration  dbms  etl 
april 2017 by jonerp
Event Report: #GoogleNext17 On Path To Enterprise Ready - by @rwang0
"Just two years ago, analysis of Google’s enterprise efforts showed very little enterprise credibility. The sales team barely understood enterprise, the products were rife with transient talent, and customers had no input into the product direction. With the recent house cleaning in the management and product teams, a commitment to enterprise by Eric Schimdt, and a host of new enterprise class alliances and partnerships, Google is rapidly building a worthwhile option for clients across the five entry points to cloud maturity."
2017  apps  strategy  artificial  intelligence  big  data  business  transformation  cdo  chief  collaboration  officer  digital  financial  hr  information 
march 2017 by jonerp
Top Tech Trends for 2017 - by @mfauscette
"Intelligent Applications: Embedding AI inside applications can enable many capabilities, but generally they fall into 2 broad categories – 1. The ability to automate tasks to relieve workers of more mundane tasks, freeing up more time for higher value activities and 2. Take large datasets and find the relevant data in some defined context, supporting business decisions."
featured  posts  technology  software  trends  &  concepts  ai  analysis  analytics  apps  ar  artificial  intelligence  big  data  business  models 
february 2017 by jonerp
MIT’s Food Computers Set the Stage for Open Source Agriculture
"There are some indications of this shift: the appearance of urban rooftop farms, an explosion of interest in automated hydroponic systems. The problem with all these systems is that their platforms are proprietary, and the lack of a common platform between them means these won’t necessarily scale up."
"Most  of  us  probably  don’t  think  too  much  about  the  foodstuffs  we  buy  in  supermarket.  But  behind  scenes  today’s  food  production  system  relies  on  a  centralized  industrial-scale  supply  chain  that’s  still  dependent  upon  soil-based  agriculture  for  majority  our  crops.Most  crops.culture  science  technology  top  stories  big  data  computer  computing  machine  learning  massachusetts  institute  open  source 
january 2017 by jonerp
Nate Silver’s Lessons for Big Data from the Unpredicted Trump Victory
"Data is not interesting for its own sake, but for how it relates to everything else. It’s like a map, you need to see how the data relates to everything else. A coordinate itself doesn’t tell you anything. But as your data set gets larger, you go from five variables to ten, you begin to see an exponential increase in complexity."
analysis  case  study  events  top  stories  big  data  futurestack  2016  new  relic 
january 2017 by jonerp
10 Use Cases in Supply Chain for Hyperledger - by @lcecere
"The Hyperledger project aims to bring together a number of independent efforts to develop open protocols and standards, by providing a modular framework that supports different components for different uses. This would include a variety of blockchain technology variants with their own consensus and storage models, and services for identity, access control, and contracts. In the Networks of Network testing in the spring of 2017, we will be using the IBM version of blockchain to test the use of hyperledger to improve network on boarding."
big  data  supply  chains  digital  chain  risk  management  safe  and  secure  visibility  blockchain  hyperledger  network  of  networks  open  source  code 
january 2017 by jonerp
Monetizing Personalized Transportation Experiences by Exploiting Big Data - by @esimoudis
"Understanding the passenger and enabling the creation of personalized transportation experiences to address the challenges brought by the introduction of ACE vehicles and Mobility Services under a new hybrid model that combines car ownership with car access, relies on a rich set of insights derived from the continuous exploitation of big data using machine intelligence. Taking advantage of these opportunities will require that incumbents accept to be in the insights-generation business rather than just in the manufacturing and distribution business."
autotech  big  data  innovation  business  model  driverless  vehicles  machine  intelligence  self  driving  cars 
january 2017 by jonerp
Not the Jetsons: 10 Use Cases for Cognitive Learning in Supply Chain - by @lcecere
"Today companies try to get very precise on imprecise data. Rows and columns define forecasting. Companies lose visibility on the patterns and demand flows. Cognitive learning solutions provide systems of insights that can combine profile pattern recognition along with learning on unstructured data. Examples include the number of google searches on an illness or symptoms, which is a predictor of the spread of an illness and subsequent prescription sales. Social sentiment on twitter and Facebook combined with point-of-sale data drives insights to understand regional sales in days. Today it takes weeks."
big  data  supply  chains  customer-centric  demand  artificial  intelligence  cognitive  learning  jetsons  machine  ontology  rules 
december 2016 by jonerp
Monday’s Musings: Secrets Behind Building Any AI Driven Smart Service - by @rwang0
"Anticipatory analytics, catalysts, and choices interact to power mass personalization at scale. Anticipatory analytics allow customers to “skate where the puck will be”. Catalysts provide offers or triggers for response. Choices allow customers to make their own decisions. Each individual or machine will have their own experience in contexts depending on identity, historical preferences, and needs at the time."
2016  adobe  ai  amazon  web  services  amazon.com  anticipatory  analytics  apple  apps  strategy  artificial  intelligence  augmented  humanity  big  data 
november 2016 by jonerp
Five Trends That Excite Me! - by @lcecere #scm
"My recommendation is for companies to stabilize their ERP spending and divert the funds into cognitive learning and artificial intelligence pilots. I think these solutions will fill in the current gaps in master data management and will be the basis of the next generation of supply chain planning. The future is autonomous planning. Today there are three primary providers: Enterra Solutions, IBM, and RuleX, but look for more competitors in this space in the near future."
big  data  supply  chains  market-driven  value  networks  chain  visibility  advanced  planning  crossgate  e2open  elementum  elemica  gtnexus  network  of  sap 
november 2016 by jonerp
HCM Fertile Ground for Data Science - by @fscavo
"Admittedly, many of these questions raise the specter of “Big Brother,” and employees may push back if they begin to feel as if they are being profiled. But with the stakes so high, can any business leader afford to not consider tools that, properly applied, could mitigate significant risks to the business?

In private conversations, some HCM providers (not necessarily the six highlighted earlier) indicate that they are thinking about how they can address these types of issues. They may not be talking about them publicly, but new applications of data science for HCM may be coming soon."
business  process  improvement  hcm  software  selection  adp  analytics  anaplan  artificial  intelligence  big  data  science  entelo  hr  hrtech 
october 2016 by jonerp
What Every Developer Should Know about Machine Learning
"For instance, how is it possible for a smartphone camera to automatically detect a face in a picture? The answer to this is also machine learning. An intelligent machine learning software application works in sync with the phone camera that allows to detect and draws boxes around the faces. This intelligence is possible when a machine learning algorithm is trained to identify faces from other objects and gives it the ability to perform decisive actions like humans."
research  technology  top  stories  algorithms  artificial  intelligence  autopilot  big  data  clustering  face  detection  google  gpu  ibm 
october 2016 by jonerp
Predictive Policing is Real; It’s Just Not Very Effective
"“It makes us smarter. It puts us on the cutting edge of what’s going on in this country,” says George Turner, the chief of the Atlanta Police Department, in a video proudly displayed on the home page for PredPol, which produces predictive policing software.

But here’s one thing that even Phillip K. Dick couldn’t even predict: Predictive Policing doesn’t really work. At least not thus far."
analysis  culture  top  stories  big  data  cardiff  university  carnegie  mellon  analsys  human  rights  group  internet  of  things  national  institute  justice  phillip  dick  predictive  analytics 
october 2016 by jonerp
Big Data Analytics Not Just for the Big Guys
"Based on our experience as consumers, it is evident that these “big guys” know how to use “big data.” But what about small to midsize companies? Like large companies, they also need to better understand the market, target their best prospects, and better serve their customers. However, in the past, they have not had the computing resources to gather and store petabytes of data, nor the internal skills to analyze all that data."
hcm  software  selection  it  strategy  adp  bi  big  data  hr  infor  microsoft  workday 
september 2016 by jonerp
Integrated Planning: Is It Rubbish? Be Careful What You Ask For. - by @lcecere
"When I ask clients what “Integrated Supply Chain Planning” means I get very different answers. Most are unclear on outcomes and what it takes to implement a planning project. There is no clear definition of integrated supply chain planning in the industry."
big  data  supply  chains  customer-centric  demand  inventory  management  sales  and  operations  planning  chain  barnes  foundation  integrated  integration  lora  cecere  simplicity  excellence 
august 2016 by jonerp
Data Integration - by @mfauscsette
""In a recent G2 Crowd survey (May 2016, N = 347), 62.2% of the respondents reported that integrating data across multiple platforms was having an impact / high impact on their current business strategy. That answer was a tie for 2nd in the overall survey for impact on strategy, with only improving customer experience scoring higher."
acquisition  business  modernization  data  decision  systems  employee  experience  networks  software  technology  big  cloud  integration  silos 
july 2016 by jonerp
Machine Learning Is Redefining The Enterprise In 2016 - by @louiscolumbus
"Exponential data growth with unstructured data being over 80% of the data an enterprise relies on to make decisions daily. Demand forecasts, CRM and ERP transaction data, transportation costs, barcode and inventory management data, historical pricing, service and support costs and accounting standard costing are just a few of the many sources of structured data enterprises make decisions with today."
business  featured  posts  technology  software  analytics  big  data  cloud  computing  enterprise  louis  columbus'  blog  machine  learning 
june 2016 by jonerp
Robotic Process Automation has now penetrated a third of enterprises - by @pfersht
"The overwhelming conclusion is that a large chunk of enterprises are actively implementing it, and 10% even claim to have full scale RPA platforms up and running (let’s not dwell too much on the finer points of defining RPA here – the bigger picture here is the obsessive widespread focus, testing and deployment of automation tools)."
2015  as-a-service  study  analytics  and  big  data  business  process  outsourcing  (bpo)  buyers'  sourcing  best  practices  cognitive  computing  hfs  surveys:  all  our  survey  posts  hfsresearch.com  homepage  it  services  robotic  automation  saas  paas 
may 2016 by jonerp
Automakers Must Partner Around Big Data - by @esimoudis
"As we are moving from a car ownership-centric to a car access-centric world where consumers increasingly demand personalized transportation solutions, automakers must augment their manufacturing and distribution expertise with broad big data management and exploitation expertise and develop a data-sharing culture."
big  data  innovation  automotive  corporate 
may 2016 by jonerp
Apache Spark for Deep Learning: Two Case Studies
"When it comes to big data-styled analytics processing, it’s a so-called two-horse race between the old stallion Hadoop MapReduce and young buck Apache Spark. Increasingly, many companies that are running in Hadoop environments are choosing to process their big data with Spark instead."
case  study  events  top  stories  apache  spark  big  data  frameworks  deep  learning  hadoop  mapreduce  machine  papi  trovit 
may 2016 by jonerp
Are You Putting Lipstick on a Pig? Or Creating New Value? - by @lcecere #scm
"Open Source needs maintenance. With the evolution of open source software, be sure that the solution you are purchasing can be maintained and evolved over time. Ask tough questions to make sure the solution can be maintained by the company selling the solution. For example, if you are buying Hadoop solutions be sure to verify the number of committers (write-back to the code base). While many consulting partners are offering open source Hadoop solutions, be sure that it is maintainable."
new  technologies  big  data  supply  chain  excellence  management 
may 2016 by jonerp
Deep Learning Demystified
"It does sound expensive and complicated, but the value of understanding the value of deep learning is invaluable. Deep learning is what makes big data more than a buzzword. Machine learning and its deeper cousin are what will give you competitive insights into your customers and then allow you to turn that into drilled-down campaigns. Deep learning has a computer learning patterns and recognizing habits that take millions in market research at which to make educated guesses."
analysis  top  stories  ai  alphago  application  programming  interface  artificial  intelligence  big  data  classic  machine  learning  deep  mind  neural  network  gpu 
april 2016 by jonerp
Rescuing BPO from its trough of directionless boredom: Make jobs challenging and creative - by @pfersht
"What’s alarming is the failure of enterprises to create and communicate a viable BPO career path for seven-out-of-eight professionals with under two years’ experience. And – while 63% of newbies strongly agree their job is vital to business performance, a depressing one-in-eight are actually excited by their career choice. "
2015  talent  in  bpo  study  analytics  and  big  data  business  process  outsourcing  (bpo)  buyers'  sourcing  best  practices  captives  shared  services  strategies  contact  center  omni-channel  crm  marketing  design  thinking  digital  transformation  finance  &  accounting  global  healthcare 
april 2016 by jonerp
Event Report: Business Transformation Top Of Mind For Microsoft Envision #ENV16 Attendees - by @rwang0
"Financial institutions and technology providers have flocked to the promises of block chain technology made famous by BitCoin. However the risk of consumer grade technologies creating security and risk issues have hampered efforts. The goal is enterprise grade block-chain technology."
2016  apps  strategy  big  data  blockchain  technology  bots  business  disruption  transformation  ceo  chatbots  chief  digital  officer  executive 
april 2016 by jonerp
Building Outside-In Processes - by @lcecere #scm
"During the afternoon, as I quietly held the pieces for Jake’s monster, my mind composed my blog post for the week. I realized that while I have spoken a lot about the need for outside-in processes, I have not helped people identify the building blocks. In this post my goal is to help companies build outside-in processes through a clearer definition."
big  data  supply  chains  customer-centric  market-driven  value  networks  chain  visibility  building  blocks  outside-in  processes  excellence  management 
april 2016 by jonerp
Trying to Figure Out New Forms of Analytics - by @lcecere #scm
"The average manufacturing company has over 150 technologies; yet, they cannot get to data. The IT environments are heterogeneous. The analyst views of use of an ERP backbone to drive analytics is quickly eroding. It is just too complex."
big  data  supply  chains  customer-centric  digital  chain  new  technologies  cloudera  every  angle  fusionops  hadoop  halo  hortonworks  analytics  excellence 
march 2016 by jonerp
It’s time we started Being As-a-Service - by @pfersht
"Our industry is beset by fear, like never before. People are scared – they know their skills and capabilities could quickly become obsolete in a world where the job openings increasingly demand creativity, analytical prowess and an ability to pivot across domains. Suddenly, if you’re not a Digital native who talks about endless disruption and the coming robo-geddon, you’re a dinosaur… The gap between hype and reality has reached ridiculous proportions, and it’s time we stopped thinking about the fantastical future and focus on what we can achieve today."
2015  as-a-service  study  analytics  and  big  data  business  process  outsourcing  (bpo)  buyers'  sourcing  best  practices  cognitive  computing  design  thinking  digital  transformation  hfsresearch.com  homepage  hr  strategy  it  services  robotic  automation 
march 2016 by jonerp
Confusion-as-a-Service: The massive disconnect between vision and reality - by @pfersht
"I have never known a time in the world of business when there is no much hype, confusion and unsettlement. Sadly, we are now living in a world where snippets of soundbites are so intensely shared across the variety media we use (I nearly said “omnichannel”) that our industry is completely dominated by hype, as opposed to reality."
2015  as-a-service  study  analytics  and  big  data  business  process  outsourcing  (bpo)  buyers'  sourcing  best  practices  confusing  information  contact  center  omni-channel  crm  marketing  design  thinking  digital  transformation  finance  &  accounting  bpo  hfs  surveys:  all  our  survey  posts  hfsresearch.com  homepage 
march 2016 by jonerp
IBM Acquiring Truven Health Analytics For $2.6 Billion And Adding It To Watson Health - by @ron_miller
"IBM announced its intent to buy Truven Health Analytics today for a whopping $2.6 billion. It is the fourth major purchase for Watson Health since the unit was established in 2014."
enterprise  tc  ibm  truven  health  analytics  healthcare  watson  big  data  mergers  and  acquisitions 
february 2016 by jonerp
The Automotive Industry’s Big Data Challenge (Part 2) - by @esimoudis
"There is significant fragmentation in the automotive world regarding data ownership. Automakers are not eager to share the data they have been collecting. Service providers in the automotive value chain have taken a similar approach. As a result, while we may have the opportunity to start establishing rich data value chains, we are not doing it."
big  data  innovation  automotive  corporate 
february 2016 by jonerp
Why 77% of the C-Suite really want provider-replacement therapy - by @pfersht
"Outsourcing is very much the direction the C-Suite wants to take to do the redesigning. 62% see a genuine need to bring in external specialists to redesign their operations, compared to only 24% of their middle layer. Clearly, leadership realizes their existing team just doesn’t have what it takes to do much more than keep the same old widgets turning."
2015  as-a-service  study  analytics  and  big  data  business  process  outsourcing  (bpo)  buyers'  sourcing  best  practices  cognitive  computing  design  thinking  digital  transformation  hr  strategy  it  services  knowledge  &  robotic  automation 
january 2016 by jonerp
Become Data Driven: Embrace the Iconoclast in Your Organization 0 by @lcecere #scm #analytics
"No company on the call felt that they had a data strategy. One company was testing a non-relational solution. While companies desire real-time systems and new insights, many were just trying to get the planning systems that they had now working better. On the call, no company thought they had cracked the code of delivering on the promise of supply chain analytics."
big  data  supply  chains  customer-centric  demand  cognitive  learning  strategy  chain  analytics  excellence 
january 2016 by jonerp
The Automotive Industry’s Big Data Challenge (Part 1) - by @esimoudis
"In the not too distant future, automakers won’t be evaluated just on the physical, safety and performance characteristics of their vehicles. Instead incumbent and next-generation automakers will be evaluated based on the completeness of their solution along five dimensions: Electric, Autonomous, Connected, Mobility Services (EAC+MS), and Information."
big  data  innovation  automotive  corporate 
january 2016 by jonerp
Netflix CEO Explains Why A "Gut" Feeling Is Still Better Than Big Data
"The CEO of one of the fastest-growing tech companies has some advice on how to make decisions with big data: Trust your gut. Speaking at DLD's flagship European conference in Munich earlier this week, Netflix's Reed Hastings says that even though the company famously invests heavily in data analytics, the ultimate decisions come down to smart intuition"
structure  big  data  netflix  analysis  leadership  reed  hastings  dld 
january 2016 by jonerp
Davos 2016 – no speed limit in pursuit of digital transformation - by @whostu
"There's a digital need and that need is speed. But how should organizations judge just how fast to drive towards digital?"
analytics  big  data  cloud  collaboration  customer  experience  general  innovation  internet  of  things  mobile  services  social 
january 2016 by jonerp
Data expires in the real-time web – RethinkDB’s co-founder on the art of open source business - by @jonerp
"RethinkDB sees a chance to change the database market through a real-time, NoSQL approach. Here's how they use an open source ecosytem to drive their business model."
big  data  databases  dev  ops  open  source 
january 2016 by jonerp
Transforming Consumer Value Chains: Navigating The Power Shift to the Shopper - by @lcecere #walmart #scm
Last week, Wal-Mart announced the closing of 269 stores and the layoffs of 10,000 employees. In addition, Macy’s announced the closure of 36 stores and K-Mart followed suite with announcements of 27 store closings. For December 2015, retail sales were the lowest since 2009. What does this mean? I think three things...."
big  data  supply  chains  customer-centric  chain  excellence  insights  community  leadership  consumer  products  ecommerce  retail  the  each 
january 2016 by jonerp
Data is eating the services industry! - by @pfersht
"In short, Dries is correct in his view that the value is no longer really in owning the software, it’s in owning and orchestrating data powered by huge internet-enabled communities. And it’s also very appropriate to take this viewpoint when we look at the future of operations and service delivery, which I’ll get to soon."
analytics  and  big  data  business  process  outsourcing  (bpo)  cognitive  computing  design  thinking  digital  transformation  it  services  knowledge  &  robotic  automation  saas  paas  iaas  bpaas 
january 2016 by jonerp
10 issues defining the services industry in 2016 - by @pfersht
"We’ve pooled all the big discussion topics from our recent service buyers summit in Harvard and let our analysts loose to demand 10 big things the industry needs to address if we are going to drag ourselves away from legacy land and avoid becoming massage therapists… and venture into the promised land of the As-a-Service Economy"
2015  hfs  buyers  summit  analytics  and  big  data  business  process  outsourcing  (bpo)  buyers'  sourcing  best  practices  cloud  computing  cognitive  contact  center  omni-channel  crm  marketing  design  thinking  digital  transformation  global  services  hr  strategy 
january 2016 by jonerp
Digital ethics, a high priority for 2016 as AI creeps into our lives - by @dahowlett
"We will need to have a robust and continuing debate on digital ethics during 2016 and beyond. The world is moving too fast to let this one slip by."
analytics  big  data  future  of  work 
december 2015 by jonerp
Why we mustn’t make the same mistakes with RPA that we made with BPO - by @pfersht
"Glaring into a future, where there is no written rule book, no set curriculum to follow, can be a little daunting. So it can’t hurt to take a look at some of the mistakes of our past to create a more long-term, focused strategy to set us in better stead as we embark on this new wave of change and disruption to our cosy little world"
featured  posts  technology  software  analytics  and  big  data  business  process  outsourcing  (bpo)  buyers'  sourcing  best  practices  cognitive  computing  design  thinking  digital  transformation  enterprise  irregulars  hfsresearch.com  homepage  it 
december 2015 by jonerp
Workday Tech Summit 2015 – fighting talk as CEO thanks Oracle - by @dahowlett
"Workday Tech Summit 2015 was packed with plenty of discussion around what makes Workday tick and why forward thinking companies should consider them as a replacement for legacy systems. Here's the financial solutions take."
analytics  big  data  collaboration  hcm 
december 2015 by jonerp
Why Spark And Hadoop Are Both Here To Stay
"At the same time, Spark is also increasingly on the scene. According to a recent survey on Spark adoption, Spark has had the most contributions of all open-source projects managed by the Apache Software Foundations over the past year. Although not as mature as Hadoop, Spark’s clear value proposition is leading to this increased investment."
structure  big  data  hadoop  apache  spark  business  intelligence  guest  posts 
december 2015 by jonerp
Big Data Still Requires Humans To Make Meaningful Connections - by @ron_miller
"Big data is a big deal, make no mistake about it, but it’s probably not as big a deal as it’s going to be eventually when we really figure out how to make good use of it. For now, we have this muddled middle where we understand the value of the data, but most organizations and governments don’t know how to use that data to its full potential."
enterprise  tc  big  data  technology 
december 2015 by jonerp
Three Reasons Why I Love Hadoop, and You Should Too! - by @lcecere
In essence, what we built through these first and second generation applications, that we term forecasting is order prediction not market forecasting. Why is this a problem? The tactical processes of forecasting in this conventional analysis cannot sense markets fast enough to slow or speed up processes."
big  data  supply  chains  demand  driven  shaping  apache  spark  hadoop  market-driven  forecasting  pig  redefinition  of  master  streaming  chain  management 
november 2015 by jonerp
Bring your own data (science) – a day with Infor’s Dynamic Science Labs at MIT - by @jonerp
"For product tire-kicking, nothing beats the on-site visit. My latest victims? Infor's Dynamic Science Labs at MIT. Here's what i learned about their startup-influenced approach to data science."
analytics  big  data  innovation  internet  of  things 
november 2015 by jonerp
Burberry CEO – digital future as important as high-end stores - by @whostu
"As Burberry heads into its 160th year in business, CEO Christopher Bailey is big on the firm's digital investment and prospects."
analytics  big  data  customer  experience  e-commerce  innovation  marketing  retail  social 
november 2015 by jonerp
The digital era that HR missed - by @brianssommer
"HR has a tough road to tread if it is to be relevant in the 21st century. Industrial age technology won't cut it anymore."
analytics  big  data 
november 2015 by jonerp
Outsourcing on life support Part I: Service providers must win back the trust of clients - by @pfersht
"Close to half the leadership we spoke to in our recent As-a-Service study view their service provider’s unwillingness to cannibalize their existing revenue model as a significant obstacle to make the As-a-Service shift, and a similar number (44%) view their provider’s lack of support to share any risk as a key issue"
2015  as-a-service  study  analytics  and  big  data  business  process  outsourcing  (bpo)  buyers'  sourcing  best  practices  cloud  computing  digital  transformation  hfsresearch.com  homepage  it  services  robotic  automation  saas  paas 
october 2015 by jonerp
Artificial intelligence can go wrong – but how will we know?
"It’s naïve to expect machines to automatically make more equitable decisions. The decision-making algorithms are designed by humans, and bias can be built in. When the algorithm for a dating site matches men with only women who are shorter than them, it perpetuates opinions and expectations about relationships. With machine learning and big data, you can end up automatically repeating historical bias in the data you’re learning from."
predictive  analytics  big  data  robotics 
october 2015 by jonerp
SAP TechEd 2015 – the wrap - by @dahowlett #saptd
"SAP's transition from on premise to cloud and subscriptions is much more than a business model. It is about an ecosystem of developers that SAP needs to nurture. TechEd 2015 gave us a glimpse of what's happening."
analytics  big  data  dev  ops  event  reports  internet  of  things 
october 2015 by jonerp
How CenterEdge went from Black Friday blues to cloud scale with Couchbase - by @jonerp
"CenterEdge faced the dreaded Black Friday site meltdown. But the story gets better - here's how their IT team used cloud and NoSQL to change their business."
analytics  big  data  event  reports  use  cases 
october 2015 by jonerp
Through the Looking Glass with Dell-EMC - by @whostu
"How many impossible things can you believe before breakfast? You might need to work up to it in the wake of the Dell-EMC merger announcement."
analytics  big  data  cloud  databases  infrastructure  innovation  internet  of  things 
october 2015 by jonerp
Cannibalize or face extinction (if you want to survive in the As-a-Service Economy) - by @pfersht
"The legacy service providers (and those service providers who may not realize they are – actually – legacy) simply don’t know how to price, solution, assess the risk and pull it all together – they can’t, because they simply aren’t set up that way."
2015  as-a-service  study  analytics  and  big  data  business  process  outsourcing  (bpo)  buyers'  sourcing  best  practices  cloud  computing  hfsresearch.com  homepage  hr  strategy  it  services  knowledge  &  robotic  automation  saas 
october 2015 by jonerp
Harman, Tech Mahindra, IBM, Accenture and Atos leading the Internet of Things phenomenon - by @pfersht
"Suddenly, IT services are morphing into “Things services”. So we decided to get ahead of this and conduct exhaustive research into how the leading service providers are shaping up their capabilities and investing in this emerging space."
analytics  and  big  data  business  process  outsourcing  (bpo)  digital  transformation  hfs  blueprint  results  hfsresearch.com  homepage  it  services  the  as-a-service  economy  internet  of  things  accenture  atos  charles  sutherland 
october 2015 by jonerp
Predictive field views and new S/4HANA scenarios – with @delvat - by @jonerp
"On the final day of SAP Controlling 2015, I asked controlling expert Julien Delvat for his thoughts on the rise of predictive analytics. He also detailed new SAP HANA and S/4 HANA use cases."
analytics  big  data  event  reports  internet  of  things 
october 2015 by jonerp
Data Driven Everything Remains Elusive - by @ron_miller
"One thing was clear at Dreamforce last week, Salesforce’s enormous customer conference — something that has become apparent to anyone paying attention. It’s becoming a data-driven world. We are awash in data, but the problem is figuring out what we are supposed to do with it."
enterprise  tc  big  data  salesforce  watson 
september 2015 by jonerp
Splunk admits open source challengers can’t be ignored, but says it has advantage - by @derek_dupreez
"There's increasing noise that Splunk faces a challenge from cheaper open source alternatives. But how much of a threat is it? Splunk's Brian Gilmore gives his perspective."
analytics  big  data  internet  of  things 
september 2015 by jonerp
Spark outpacing Hadoop? Survey says yes - by @dahowlett
"Databricks survey of Spark usage provides insights into an open source platform that supports multiple languages and use platforms. This is very promising for the future of big data and streaming analytics."
analytics  big  data 
september 2015 by jonerp
Eight takeaways from prof Andy McAfee’s second machine age discussion - by @dahowlett
"The Second Machine Age is upon us. What matters now is our capacity to embrace what it means beyond the buzzwords that go with it."
analytics  big  data  bpo  collaboration 
september 2015 by jonerp
Using the Bits: Building Digital Outside-In Processes - by @lcecere
"CRM and SRM Are Not the Adapters to Build the End-t0-End Value Chain. Customer relationship management (CRM) and supplier relationship management (SRM) are enterprise applications. They are not suitable connectors for B2B networks. The connections to B2B networks need to be based on trading partner synchronization and harmonization of data through the use of canonical infrastructures."
big  data  supply  chains  demand  driven  sensing  shaping  digital  chain  market-driven  outside-in  processes  sentiment  analysis  insights  global  summit 
september 2015 by jonerp
Long live the freemium analyst model… - by @pfersht
"It seems the “freemium” model we’ve adopted at HfS over the last six years is really having an impact. It’s our view that top insights shouldn’t be stuffed behind a firewall. Clients will pay for premium data, indepth analyst strategy session and in-depth competitive landscape reports, but when it comes to insights, viewpoints, or just some plain old entertainment, why hide it?"
analytics  and  big  data  business  process  outsourcing  (bpo)  hfsresearch.com  homepage  it  services  advisors  enterprise  irregulars  hfs 
september 2015 by jonerp
The best cure for analytics and IoT hype is field work – with @vijayasankarv - by @jonerp
"What's a good way to get a handle on big data and IoT hype? Talk to someone like IBM's Vijay Vijayasankar, who is knee deep in customer delivery. Here's some highlights from our recent video hangout."
analytics  big  data  internet  of  things  marketing  services 
september 2015 by jonerp
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