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Big Data Myths...BUSTED

Jen Cohen Crompton

Since Big Data is such a “big” and diverse topic, there are plenty of assumptions, misunderstandings, and confusion surrounding the concept. Through discussions with colleagues, I’ve noticed a few recurring themes, uncertainties and generalizations. I’ve also heard plenty of assumptions and claims…some of which are true and some lack validity. After hearing from industry experts, I’ve compiled three Big Data Myths, which we will bust, to uncover some of the Big Data facts.

Myth One: Big Data is really “BIG.”

When it is stated that big data is really big, that infers that big data translates into a lot of information, more than most companies collect. In that case, this myth is not true at all. At the latest Hadoop conference, big data was defined as any data that cannot fit into Excel, which in reality, is the amount of data most companies collect and store, especially since the rise in social media and the volumes of data collected from those sources.

“Social media releases floods of data that hold massive promises for business – both in terms of branding and opening up new channels to market, in which large populations of consumers are speaking. They’re [consumers] communicating who they are and what they do and do not like. Such a relentless flow of data provides extraordinary levels of feedback and an unrivaled chance for companies to listen to the voices of their customers and target audience(s), garner intelligence, and participate in a collaborative dialogue to boost competitive advantage and new opportunity,” explains Upasna Gautam of MagicLogix.com. [Stay tuned for another post about the link between social media and big data.] Most businesses are using social media outlets for this type of insight and the amount of data collected and needed to be analyzed is considered “big.”

So it isn’t just enterprises who are struggling to manage big data. The general rule – if you have multiple spreadsheets with data, you have big data on your hands. As Margaret Dawson, VP of Marketing for Symform points out, “SMBs also struggle to keep up with skyrocketing data volumes. In fact, a recent data and backup trends survey of SMBs found that respondents average one terabyte to over 500 TBs (1 TB = 1000 GB) of data, with most forecasting data growth of 10-40% over the next year.” Wow.

Myth Two: Big Data makes BETTER analytics.

Is bigger really better? Sometimes, but in the case of big data, it seems that in certain circumstances, bigger is simply bigger and quantity does not always equal quality; the gap occurs in the analysis and translation of the data. It’s [almost] comparable to giving someone a hammer, nails, wood, and all the tools they need to build a house, but without the blueprint, they don’t know what to do and where to start. This means that with our data, we have to be sure we are collecting the valuable data to help solve the most prominent problems – the problems that relate back to our KPIs and bottomlines – and following the right blueprint to get what we need.

Erin Bartolo, Data Science Program Manager at the School of Information Studies at Syracuse University, agrees and provides a strategy to ensure bigger data turns into something meaningful. “Entertain your inner skeptic by questioning everything from what data are meaningful to how you project your own biases on findings. Without objective, analytical skills, analytics merely backs up our own biases with data,” she advises. She explains that the “whys” and “hows” need to be infused into the data analysis to really find value. She says, “…increasing one’s awareness of data and appreciation of its objectivity reveals insights whether the data is stored in an Excel spreadsheet or in a massive data warehouse.”

So in this case, size doesn’t really matter, unless you need the size of the data to answer the questions that relate back to your ultimate goals.

Myth Three: You need a team of Hadoop engineers and Analytics platforms to be on premise to work with Big Data.

While it is quite a challenge to merge data collected from various sources and analyze the information (and Hadoop professionals could be an advantage), there are other solutions and platforms that can help transform the unstructured data into structured data and merge with business intelligence (BI) tools.

Werner Hopf, CEO, Dolphin believes, “There are compelling [software] solutions to help companies meet those goals, achieve significant savings and performance improvements, and lay the foundation for leveraging SAP HANA – the vehicle for truly maximizing the potential benefits of big data – in the future.” These options can be cost effective and easily navigated by an intelligent, but not expert users.

The other idea of housing analytics platforms on premise is busted by Keith Metcalfe, Vice President of Sales and Marketing at WCI Consulting as he adds, “Integrating and cleansing data to a targeted place for reporting is a core concept behind any enterprise approach to analytics/business intelligence, and there is no technical reason why that target cannot reside in a hosted/SaaS environment. Cloud platforms and analytics tools are great applications for hosted (e.g. Amazon Web Services) or SaaS analytics platforms (e.g. SAP BusinessObjects BI OnDemand). Having said this, core to the topic of SaaS and hosted environments is that an organization sees value in replacing IT infrastructure, as this is where the financial return justifies the cost of investing in such environments.”

Two last pieces of big data management advice from Hopf, “From a data management perspective, making the most of the big data opportunity requires the adoption of two key strategies: 1) augmenting data archiving capabilities with nearline storage; and 2) re-architecting the business warehouse (BW) data model for lean, flexible, organized “views” of information that serve up agile reporting without increasing administrative
overhead.” Do this, add the human aspect, and solve big business problems using your big data.

If you have questions about these myths, feel free to reach out to a Top Big Data Twitter Influencers.

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About Jen Cohen Crompton

Jen Cohen Crompton is a SAP Blogging Correspondent reporting on big data, cloud computing, enterprise mobility, analytics, sports and tech, and anything else innovation-related. When she's not blogging, she can be caught marketing, using social media and/or presenting at conferences around the world. Disclosure: Jen is being compensated by SAP to produce a series of articles on the innovation topics covered on this site. The opinions reflected here are her own.

Why 3D Printed Food Just Transformed Your Supply Chain

Hans Thalbauer

Numerous sectors are experimenting with 3D printing, which has the potential to disrupt many markets. One that’s already making progress is the food industry.

The U.S. Army hopes to use 3D printers to customize food for each soldier. NASA is exploring 3D printing of food in space. The technology could eventually even end hunger around the world.

What does that have to do with your supply chain? Quite a bit — because 3D printing does more than just revolutionize the production process. It also requires a complete realignment of the supply chain.

And the way 3D printing transforms the supply chain holds lessons for how organizations must reinvent themselves in the new era of the extended supply chain.

Supply chain spaghetti junction

The extended supply chain replaces the old linear chain with not just a network, but a network of networks. The need for this network of networks is being driven by four key factors: individualized products, the sharing economy, resource scarcity, and customer-centricity.

To understand these forces, imagine you operate a large restaurant chain, and you’re struggling to differentiate yourself against tough competition. You’ve decided you can stand out by delivering customized entrees. In fact, you’re going to leverage 3D printing to offer personalized pasta.

With 3D printing technology, you can make one-off pasta dishes on the fly. You can give customers a choice of ingredients (gluten-free!), flavors (salted caramel!), and shapes (Leaning Towers of Pisa!). You can offer the personalized pasta in your restaurants, in supermarkets, and on your ecommerce website.

You may think this initiative simply requires you to transform production. But that’s just the beginning. You also need to re-architect research and development, demand signals, asset management, logistics, partner management, and more.

First, you need to develop the matrix of ingredients, flavors, and shapes you’ll offer. As part of that effort, you’ll have to consider health and safety regulations.

Then, you need to shift some of your manufacturing directly into your kitchens. That will also affect packaging requirements. Logistics will change as well, because instead of full truckloads, you’ll be delivering more frequently, with more variety, and in smaller quantities.

Next, you need to perfect demand signals to anticipate which pasta variations in which quantities will come through which channels. You need to manage supply signals source more kinds of raw materials in closer to real time.

Last, the source of your signals will change. Some will continue to come from point of sale. But others, such as supplies replenishment and asset maintenance, can come direct from your 3D printers.

Four key ingredients of the extended supply chain

As with our pasta scenario, the drivers of the extended supply chain require transformation across business models and business processes. First, growing demand for individualized products calls for the same shifts in R&D, asset management, logistics, and more that 3D printed pasta requires.

Second, as with the personalized entrees, the sharing economy integrates a network of partners, from suppliers to equipment makers to outsourced manufacturing, all electronically and transparently interconnected, in real time and all the time.

Third, resource scarcity involves pressures not just on raw materials but also on full-time and contingent labor, with the necessary skills and flexibility to support new business models and processes.

And finally, for personalized pasta sellers and for your own business, it all comes down to customer-centricity. To compete in today’s business environment and to meet current and future customer expectations, all your operations must increasingly revolve around rapidly comprehending and responding to customer demand.

Want to learn more? Check out my recent video on digitalizing the extended supply chain.

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Hans Thalbauer

About Hans Thalbauer

Hans Thalbauer is the Senior Vice President, Extended Supply Chain, at SAP. He is responsible for the strategic direction and the Go-To-Market of solutions for Supply Chain, Logistics, Engineering/R&D, Manufacturing, Asset Management and Sustainability at SAP.

How to Design a Flexible, Connected Workspace 

John Hack, Sam Yen, and Elana Varon

SAP_Digital_Workplace_BRIEF_image2400x1600_2The process of designing a new product starts with a question: what problem is the product supposed to solve? To get the right answer, designers prototype more than one solution and refine their ideas based on feedback.

Similarly, the spaces where people work and the tools they use are shaped by the tasks they have to accomplish to execute the business strategy. But when the business strategy and employees’ jobs change, the traditional workspace, with fixed walls and furniture, isn’t so easy to adapt. Companies today, under pressure to innovate quickly and create digital business models, need to develop a more flexible work environment, one in which office employees have the ability to choose how they work.

SAP_Digital_Emotion_BRIEF_image175pxWithin an office building, flexibility may constitute a variety of public and private spaces, geared for collaboration or concentration, explains Amanda Schneider, a consultant and workplace trends blogger. Or, she adds, companies may opt for customizable spaces, with moveable furniture, walls, and lighting that can be adjusted to suit the person using an unassigned desk for the day.

Flexibility may also encompass the amount of physical space the company maintains. Business leaders want to be able to set up operations quickly in new markets or in places where they can attract top talent, without investing heavily in real estate, says Sande Golgart, senior vice president of corporate accounts with Regus.

Thinking about the workspace like a designer elevates decisions about the office environment to a strategic level, Golgart says. “Real estate is beginning to be an integral part of the strategy, whether that strategy is for collaborating and innovating, driving efficiencies, attracting talent, maintaining higher levels of productivity, or just giving people more amenities to create a better, cohesive workplace,” he says. “You will see companies start to distance themselves from their competition because they figured out the role that real estate needs to play within the business strategy.”

The SAP Center for Business Insight program supports the discovery and development of  new research-­based thinking to address the challenges of business and technology executives.

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Sam Yen

About Sam Yen

Sam Yen is the Chief Design Officer for SAP and the Managing Director of SAP Labs Silicon Valley. He is focused on driving a renewed commitment to design and user experience at SAP. Under his leadership, SAP further strengthens its mission of listening to customers´ needs leading to tangible results, including SAP Fiori, SAP Screen Personas and SAP´s UX design services.

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What If Chelsea Manager Jose Mourinho Could Be Proved Right In Medical Staff Row?

Mark Goad

Big Data and the Internet of Things brings new level of insight to sports medicine

With the 2015-16 European football (soccer) season underway, we are already seeing the impact of the huge pressure to succeed. In some cases, it is boiling over even this early on, with Chelsea manager Jose Mourinho getting involved in a very public row with his medical staff over the treatment of Eden Hazard during a match. As the season builds momentum, all clubs know one of the most vital aspects of winning trophies is keeping the best players fit so they can play at the top of their game as often as possible.

Last season, just like in every season, we saw injuries that affected teams’ results and possibly their final standings at the end of the season, while other teams capitalized. Arsenal manager Arsene Wenger blamed injuries for the team’s failed title bid, while Real Madrid suffered injuries to players like Gareth Bale and Luka Modric at a crucial stage of the season and lost the title to Barcelona.

There’s no doubt that football clubs, especially the bigger teams, employ first-rate medical staff – physiotherapists, doctors, sports scientists, and so on – but they can only do so much to keep players off the treatment table. Players are human, after all, and keeping them injury-free for such long and grueling campaigns is a big ask. This season again will see players on the end of crunching tackles, over-exerting their bodies, and over-stretching.

What’s less talked about than lost games and league titles when discussing injuries is the salaries paid to injured players. The estimated average cost of player injuries in the top four professional football leagues in 2015 was $12.4 million* per team. Remarkably, every year teams lose an equivalent of 15%-30%** of their player payroll to injuries.

As salaries continue to rise, injuries are becoming just as much of an off-the-pitch boardroom issue as they are an on-the-pitch issue. Consider that if Barcelona’s Lionel Messi, the world’s highest-paid player, spends just a week out injured, the club still has to pay his weekly salary of around $1 million. Not only that, but there’s the huge potential for lost revenue from missing out on UEFA Champions League progress or domestic success because key players are out.

Just as winning seems to mean more than ever, so does football as a business. So with the spotlight firmly on “sweating the assets” – extracting maximum value from the entire squad – clubs are looking to Big Data and Internet of Things technology to consider how player injuries can be prevented with new levels of insight.

Prevention is better than cure

In July this year we saw what could be a huge landmark in the potential of monitoring the risk of injuries, when football’s international governing body FIFA announced its approval of wearable electronic performance and tracking systems during matches. As well as collecting data on statistics like distance covered and heart rate to determine decisions like substitution timings, this also paves the way for wearable satellite devices that keep medical staff updated on the likelihood of a player picking up an injury from over-exertion.

Emerging injury-risk monitoring software uses the concepts of Big Data and wearable technology to pull in and apply mathematical formulas to an exhaustive range of relevant data about players: fitness levels, recent levels of exertion, opponents, age, technique, hydration, even weather. This could help medical staff predict the risk of future injuries with much greater accuracy, allowing them to run simulations and take corrective actions in real time. Imagine a seemingly non-injured key player being substituted during a tightly contested match, only to find out afterwards that monitoring software had indicated he was at a high risk of pulling a muscle. This could very much be a part of the future of professional football.

Going back to Jose Mourinho and his reaction to the Chelsea medical staff running onto the pitch to treat Eden Hazard, it’s interesting to consider how in the future this kind of technology could either support or discredit his position in the dispute. It could help managers work more closely with physiotherapists, as they can visualize the data that shows the risk of injury to players. Although the pressure to win will likely keep on rising, the risk of expensive players injuries could see a big reduction.

SAP’s own injury risk monitoring software is currently in the proof-of-concept phase and will be entering development in the near future. The goal is to build IRM on the SAP Sports One platform as an additional component, and to provide integration to the existing modules of SAP Sports One solution. SAP Sports One was launched earlier this year and is the first sports-specific cloud solution powered by the SAP HANA platform, providing a single, unified platform for team management and performance optimization.

*Statistic calulated using 2015 Global Sports Salaries Survey

**Bleacher Report “Inside the 2014 Numbers of Each MLB Team’s Regular-Season Injury Impact” and NBA Injury Analysis

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Mark Goad

About Mark Goad

Mark Goad is a Client Partner at SAP. His specialties include social media, digital marketing, analytics, strategy and management.

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Big, Bad Data: How Talent Analytics Will Make It Work In HR

Meghan M Biro

Here’s a mind-blowing fact: Research from IBM shows that 90% of the data in the world today has been created in the last two years alone. I find this fascinating.

Which means that companies have access to an unprecedented amount of information: insights, intelligence, trends, future-casting. In terms of HR, it’s a gold mine of Big Data.

This past spring, I welcomed the Industry Trends in Human Resources Technology and Service Delivery Survey, conducted by the Information Services Group (ISG), a leading technology insights, market intelligence, and advisory services company. It’s a useful study, particularly for leaders and talent managers, offering a clear glimpse of what companies investing in HR tech expect to gain from their investment.

Not surprisingly, there are three key benefits companies expect to realize from investments in HR tech:

• Improved user and candidate experience

• Access to ongoing innovation and best practices to support the business

• Speed of implementation to increase the value of technology to the organization.

It’s worth noting that driving the need for an improved user interface, access, and speed is the nature of the new talent surging into the workforce: people for whom technology is nearly as much a given as air. We grew up with technology, are completely comfortable with it, and not only expect it to be available, we assume it will be available, as well as easy to use and responsive to all their situations, with mobile and social components.

According to the ISG study, companies want HR tech to offer strategic alignment with their business. I view this as more about enabling flexibility in talent management, recruiting and retention — all of which are increasing in importance as Boomers retire, taking with them their deep base of knowledge and experience. And companies are looking more for the analytics end of the benefit spectrum. No surprise here that the delivery model will be through cloud-based SaaS solutions.

Companies also want:

• Data security

• Data privacy

• Integration with existing systems, both HR and general IT

• Customizability —to align with internal systems and processes.

Cloud-based. According to the ISG report, more than 50% of survey respondents have implemented or are implementing cloud-based SaaS systems. It’s easy, it’s more cost-effective than on-premise software, and it’s where the exciting innovation is happening.

Mobile/social. That’s a given. Any HCM tool must have a good mobile user experience, from well-designed mobile forms and ease of access to a secure interface.

They want it to have a simple, intuitive user interface – another given. Whether accessed via desktop or mobile, the solution must offer a single, unified, simple-to-use interface.

They want it to offer social collaboration tools, which is particularly key for the influx of Millenials coming into the workplace who expect to be able to collaborate via social channels. HR is no exception here. While challenging from a security and data protection angle, it’s a must.

But the final requirement the study reported is, in my mind, the most important: analytics and reporting. Management needs reporting to know their investment is paying off, and they also need robust analytics to keep ahead of trends within the workforce.

It’s not just a question of Big Data’s accessibility, or of sophisticated metrics, such as the key performance indicators (KPIs) that reveal the critical factors for success and measure progress made towards strategic goals. For organizations to realize the promise of Big Data, they must be able to cut through the noise and access the right analytics that will transform their companies for the better.

Given what companies are after, as shown in the ISG study, I predict that more and more companies are going to be recognizing the benefits of using integrated analytics for their talent management and workforce planning processes. Talent analytics creates a powerful, invaluable amalgam of data and metrics; it can identify the meaningful patterns within that data and metrics and, for whatever challenges and opportunities an organization faces, it will best inform the decision makers on the right tactics and strategies to move forward. It will take talent analytics to synthesize Big Data and metrics to make the key strategic management decisions in HR. Put another way, it’s not just the numbers, it’s how they’re crunched.

For more on the power of talent analytics, see Talent Analytics: Predicting HR’s Way Out Of The Fog.

Image source: Simonebrunozzi via Wikipedia

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