Sections

Top Five Big Data Challenges For CIOs

Daniel Newman

Big Data is more than just a buzzword these days – but it can be both a massive opportunity and a huge problem for companies. Digital data collection has been a practice since the dawn of computing, but the exponential increase of information, in terms of smartphones, social, search, and the Internet of Things, have created a snowball effect when it comes to the data that’s generated, collected, and stored. What’s that mean? It means lots of possibilities for smarter products and services, smarter marketing, and smarter business practices. It means 88% of executives say Big Data is a top priority for their company. But it also means lots of challenges are coming their way.

The amount of data we create each year creates a staggering set of problems for those who are in charge of managing it. Thankfully, we’re no longer in an era where one person has all the collective responsibility for an organization’s data. That said, the CIO is most often tasked with developing systems of record that can leverage tech to drive better business processes.

We know CIOs face innumerable challenges when it comes to Big Data, but what are the biggest Big Data challenges for CIOs in 2016? Let’s break down.

  1. Collection. The challenge with collection doesn’t have to be the obvious one (how do we collect it)? What if, as Clorox’s CIO Manjit Singh discussed in an interview on the very subject, it was something more high level, like “how to get insight out of the data – what questions to ask and how to use the data to predict results in the business?” Singh is right. CIOs should ask themselves what data is important to collect from a business case standpoint? What data isn’t? How is it decided? CIOs can start by looking at Big Data collection from a big picture perspective.
  1. Storage. Logic states that Big Data requires some big attention to storage, and it’s the truth. Besides the sheer volume requirements of all those bytes, certain data also needs to be available on demand at any time. This can be for operations purposes or compliance. Even though storage is more available than ever, it isn’t all created equal. CIOs should examine infrastructure and cloud options thoroughly before any checks are signed. Purchasing too much is wasting money, but too little could mean crashes and costly downtime.
  1. Organization and management. To make data useful, it needs to not just be stored and accessible but organized in some way that makes it easy to find and easy to pull. That way, data scientists and other users can locate, analyze, and apply the information in a way that is both efficient and measurable.
  1. Conversion. With companies turning to more and more chief data officers, architects, and analysts, it is critical that business intelligence tools are readily available these individuals. While they may be involved in selecting the tools for creating business intelligence, the CIO needs to have systems in place – systems for collection, storage, organization, and management – so they can actually use them.

I’m sure I don’t have to tell you that internal infrastructure costs money, and many organizations want results from Big Data initiatives sooner rather than later. In these instances where financial and analytical expectations don’t jive – and in a ton of other Big Data situations, too – CIOs who have not yet done so should consider taking a look at cloud-based options, especially in the realm of increased operability provided by software-as-a-service (SaaS).

  1. Unstructured data growth. Big Data is more than just data produced by and for a company. Even when consumers aren’t interacting specifically with a brand – when they’re making posts on social media, uploading videos, or generating any other type of personalized content – they’re giving businesses insight into their habits, preferences, and consumer behaviors. Even when it’s not explicitly tied to their business pages or endeavors – perhaps, actually, especially when it’s not – CIOs need to develop systems to collect, store, organize, and make this valuable customer data usable for operations, sales, and marketing.

Big Data has already had a substantial impact on the way businesses operate internally, interact with consumers, and navigate their respective markets. That Big Data snowball keeps rolling, though, and even more changes are forthcoming. If you’re a CIO who can conquer the challenges above without losing sight of the opportunities success will bring, 2016 will be a great year.

See The Digital Economy Infographic to learn more about how hyperconnectivity is changing the way we live and work, how businesses operate, and how society functions.

Comments

About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

Tags:

CIO

Real-Time Data Transforms Political Journalism, But Context Remains Vital

John Graham

The runup to the 2016 U.S. election is being covered in interesting new ways by the political media, with analysis of Big Data and real-time opinion polling offering journalists much deeper insight than ever before. The trend of “data journalism” is peaking as the media embraces advanced technologies that allow them to deliver a new breed of numbers-driven, fact-based journalism.

The tools being used for data journalism open up possibilities for fresh perspectives, more in-depth reporting, and new stories behind the numbers that have never been seen before. Traditional journalists are beginning to see how data journalism can complement their reporting, and the U.S. election is serving as an ideal testing ground. Political reporters are lapping up the improved data literacy and access to objective analysis, which is helping to make their reports more thorough and informative.

Consequently, American voters are becoming digital voters. They have access to real-time, data-driven information and public sentiment, which is empowering them with broader insight. They’re relying on this to help them make up their minds before they cast their vote, and it’s given many voters a renewed interest in becoming informed citizens able to make an educated choice.

However, the rise of data-driven journalism brings with it a potential pitfall for media organizations and readers alike. Digital information overload will bring about a fatigue around numbers if reporting quantity becomes more highly valued than quality. Having access to mountains of data is a huge benefit, but a reporter still has to be a journalist first to ensure they’re not getting buried under the numbers and missing the stories.

In other words, a political journalist still needs to be a politico, not just a statistician. They could fall into the trap of placing too much importance on meaningless correlations as indicators of voter sentiment, losing their grasp on what made them a great political reporter in the first place. As data gets bigger, this will become harder to resist. So they need to become experts in making Big Data small—rather than obsessing over the numbers, obsessing over figuring out what they really mean. In doing that, they have an unprecedented opportunity to make people more informed rather than simply overwhelming with them a series of conflicting data sets.

Some media organizations are already tackling the challenge of remaining relevant in a world of information overload. Using big data and visualizations, they are making great strides in making data journalism more accessible to reporters, politicos, and voters, which is proving its worth in giving political reporting a new lease of life.

Reuters’ Polling Explorer tool is an example of how this is being done, offering up customizable data visualizations focusing on the biggest talking points in the U.S. leading up to the election. It’s an entirely new scale of public opinion measurement, presented in a way anyone can understand and use, while enabling Reuters to usher in its own improved brand of accurate, fact-based, and timely journalism.

We can see the true potential of using real-time data analysis to measure up-to-the-minute public opinion in one poll on the most important problem facing the US today. Immediately after the Paris attacks in November, terrorism skyrocketed way above the economy as the number-one issue, rising sharply again straight after the December San Bernardino attack. For Reuters, this is just one of many examples of their greatly increased ability to find outliers in the data.

Reuters Polling Explorer runs on SAP HANA, an in-memory data platform that allows Reuters to access and analyze 100 million survey responses for quicker and more efficient reporting of public opinion.

For more on data analytics in today’s media environment, see How Big Data Is Changing The News Industry.

Comments

John Graham

About John Graham

John Graham is president of SAP Canada. Driving growth across SAP’s industry-leading cloud, mobile, and database solutions, he is helping more than 9,500 Canadian customers in 25 industries become best-run businesses.

Smart Machines Create Markets For Cyber-Physical Advances

Marion Heindenreich

Today, industrial machines are more intelligent than ever before. These intelligent machines are changing companies in many ways.

Why smart machines?

Mobile networked computers were a key breakthrough for making smart machines. Big Data allows machines and computers to store information and analyze complex patterns. Cloud computing offers broad access to information and more storage.

These computerized machines are both physical and virtual. Some call them “cyber-physical” machines. Technology lets them be self-aware and connected to each other and larger systems.

Businesses change their approaches

Intelligent machines allow companies to innovate in many areas. For one, the value proposition for customers is evolving. Businesses now model and plan in different ways in many industries.

Makers of industrial machines and parts work in new ways within the organization. Engineering now partners with mechanical, electronic, and software staff to develop new products. Manufacturing now seamlessly ties what happens on the shop floor to the customer.

Service models are changing too. Scheduled and reactionary servicing of machines is fading. Now intelligent machines track themselves. Machines detect problems and report them automatically. Major problems or failures are predicted and reported.

A data mining example

One good industrial example is mining, which can be dangerous and difficult. As ores become scarce, the costs of mining have increased.

“Smart machines” started in mining in the late 1990s. Software and hardware let remote users change settings. Operators moved hydraulic levers from a safe distance. Sensors observed performance and diagnosed issues.

Data cables connected machines to computers on the surface. Continuous and remote monitoring of the machines grew. Over time, embedded sensors helped improve monitoring, diagnostics, and data storage.

The technology means workers only go underground to fix specific issues. As a result, accident and injury risk is lower.

New wireless technology now lets mining companies connect data from many mine sites. Service centers access large amounts of data and can improve performance. Maintenance is prioritized and equipment downtime is reduced.

Opportunity abounds

For companies the time is now. Today, mobile “connected things” generate 17% of the digital universe. By 2020 that share grows to 27%.

You might not be investing in this so-called “Internet of Things” (devices that connect to each other). But it’s a good bet your competitors are. A December 2015 study reported 33% of industrial companies are investing in the Internet of Things. Another 25% are considering it.

There are risks

This new dawning era of manufacturing is exciting. But there are concerns. Cyber attacks on the Internet of Things are not new. But as the use of intelligent machines grows, the threat of cyber attacks in industry grows.

Data confidentiality and privacy are concerns. So too are software and hardware vulnerabilities. Exposure to attack lies not just in the virtual space but the physical too. Tampering with unattended machines and theft pose serious risk.

To address these threats, industries must invest in cybersecurity along with smart machines.

Conclusion

The potential advantages of smart machines are staggering. They can reshape industries and change how companies produce new products and create new markets.

For more information, please download the white paper Digital Manufacturing: Powering the Fourth Industrial Revolution.

Comments

Marion Heindenreich

About Marion Heindenreich

Marion Heidenreich is a solution manager for the SAP Industrial Machinery and Components Business Unit who focuses on solution innovations like Product Costing on SAP HANA and cloud solutions, as well as providing financial and business analysis for industry business strategy definition and business planning.

Robots: Job Destroyers or Human Partners? [INFOGRAPHIC]

Christopher Koch

Robots: Job Destroyers or Human Partners? [INFOGRAPHIC]

To learn more about how humans and robots will co-evolve, read the in-depth report Bring Your Robot to Work.

Download the PDF (91KB)

Comments

About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

Tags:

What Is The Key To Rapid Innovation In Healthcare?

Paul Clark

Healthcare technology has already made incredible advancements, but digital transformation of the healthcare industry is still considered in its infancy. According to the SAP eBook, Connected Care: The Digital Pulse of Global Healthcare, the possibilities and opportunities that lie ahead for the Internet of Healthcare Things (IoHT) are astounding.

Many health organizations recognize the importance of going digital and have already deployed programs involving IoT, cloud, Big Data, analytics, and mobile technologies. However, over the last decade, investments in many e-health programs have delivered only modest returns, so the progress of healthcare technology has been slow out of the gate.

What’s slowing the pace of healthcare innovation?

In the past, attempts at rapid innovation in healthcare have been bogged down by a slew of stakeholders, legacy systems, and regulations that are inherent to the industry. This presents some Big Data challenges with connected healthcare, such as gathering data from disparate silos of medical information. Secrecy is also an ongoing challenge, as healthcare providers, researchers, pharmaceutical companies, and academic institutions tend to protect personal and proprietary data. These issues have caused enormous complexity and have delayed or deterred attempts to build fully integrated digital healthcare systems.

So what is the key to rapid innovation?

According to the Connected Care eBook, healthcare organizations can overcome these challenges by using new technologies and collaborating with other players in the healthcare industry, as well as partners outside of the industry, to get the most benefit out of digital technology.

To move forward with digital transformation in healthcare, there is a need for digital architectures and platforms where a number of different technologies can work together from both a technical and a business perspective.

The secret to healthcare innovation: connected health platforms

New platforms are emerging that foster collaboration between different technologies and healthcare organizations to solve complex medical system challenges. These platforms can support a broad ecosystem of partners, including developers, researchers, and healthcare organizations. Healthcare networks that are connected through this type of technology will be able to accelerate the development and delivery of innovative, patient-centered solutions.

Platforms and other digital advancements present exciting new business opportunities for numerous healthcare stakeholders striving to meet the increasing expectations of tech-savvy patients.

The digital evolution of the healthcare industry may still be in its infancy, but it is growing up fast as new advancements in technology quickly develop. Are you ready for the next phase of digital transformation in the global healthcare industry?

For an in-depth look at how technology is changing the face of healthcare, download the SAP eBook Connected Care: The Digital Pulse of Global Healthcare.

See how the digital era is affecting the business environment in the SAP eBook The Digital Economy: Reinventing the Business World.

Discover the driving forces behind digital transformation in the SAP eBook Digital Disruption: How Digital Technology is Transforming Our World.

Comments

About Paul Clark

Paul Clark is the Senior Director of Technology Partner Marketing at SAP. He is responsible for developing and executing partner marketing strategies, activities, and programs in joint go-to-market plans with global technology partners. The goal is to increase opportunities, pipeline, and revenue through demand generation via SAP's global and local partner ecosystems.