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Big Data For The Little Guy

Susan Kuchinskas

SME owner analyzes Big DataBig data is the biggest of business buzzwords, but unlike many buzzwords, it has plenty of substance behind it. The idea is that mining vast repositories of raw data can uncover patterns that lead to competitive insights. Walmart’s been doing this for decades, analyzing its cash register traffic in real time to shave every last ounce of waste from its retail operations.

According to McKinsey, the amount of data generated globally is growing by 40 percent each year. No wonder: Facebook alone generates 10 terabytes of data each day. Speaking of Facebook, it’s crunching that data to fine-tune its ad targeting—and up its market cap. A report by Intuit and Emergent Research, THE NEW DATA DEMOCRACY: How Big Data Will Revolutionize the Lives of Small Businesses and Consumers, says data is a new kind of raw material that’s as important as labor or capital, with even greater potential.

“Digital data will turbocharge the use of analytics, in both small and large businesses,” the report predicted. “Proprietary data combined with data from the cloud will create new insights and a deeper understanding of what consumers need, what they like and what will keep them happy. The development of new data sources and unique analytics will drive entrepreneurial growth around the globe over the coming decade.”

But big data isn’t just for big companies like Walmart and Facebook, according to Steve King, a partner at Emergent Research and the author of the report. King says that, in the same way that Amazon uses its massive databases to recommend books and movies to individuals, small businesses will be able to use their data to better understand individual customers—and offer more personalized service than giant chains.

Data crunching on the cheap

To take advantage of big data, “You don’t have to have high-end machinery and data scientists,” King says. There are plenty of third-party services that offer analytics services for free:

  • Quantcast: Measures and analyzes your traffic with demographic and geographic information. You can compare your site to others to see how you stack up.
  • Google Analytics: Customizable reports show which parts of your website are performing well, which pages are most popular, what sites visitors came from, and what search terms sent traffic to a page.
  • WebTrends Reinvigorate: Offers sophisticated charting and reports in real time so you can, for example, track the results of an online promotion. The starter subscription is $10 a month with a 14-day free trial.
  • Your web hosting service: Most offer at least basic traffic analysis. Have you ever looked at this?

The first step is identifying what data you can collect. “Go through each functional area of your business,” King advises. You don’t need to have a really big data set. Any information that you haven’t analyzed before is grist for the big data mill. For example, “It’s amazing how many small businesses with websites don’t bother to analyze their web traffic,” King says.

Customer relationship management systems, known as CRMs, are an easy way to get all your customer information into one database. This information can be shared across the company, and different divisions can feed information back into it. CRMs can be acquired cheaply or for free. For example, Zoho CRM and Insightly are free for up to three users.

King suggests that you start simple. Accountants usually have a handle on important metrics and are used to working with data. “Meet with your accountant and figure out what the key performance indicators are for your company, track them, and grow from there,” he advises.

You can’t afford to ignore data these days. When Emergent Research first studied the impact of web analytics on corporate competitiveness in 2007, it found that it made little difference: The skill of business owners and executives outweighed technology as indicators of business success.

No longer. Now, Emergent’s research shows companies that successfully use analytics are beginning to outperform those that do not. While many managers found success by relying on their experience and gut instincts, “The world has gotten faster and more complex,” King says. “They will need—more and more—to add analytics to that intuition, or they’ll fall behind.”

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About Susan Kuchinskas

Susan Kuchinskas covers business strategy, technology and culture. She's the author of two books, Going Mobile: Building the Real-Time Enterprise with Mobile Applications that Work, and The Chemistry of Connection: How the Oxytocin Response Can Help You Find Trust, Intimacy and Love. When she isn't scoping out ways to do things better, faster and more engagingly, she digs in her organic garden and watches her bees.

From Oxcart To Hyperloop: The Digital Transformation Of Travel

Sandeep Raut

Years ago, planning a vacation involved visits to travel agents, browsing printed travel brochures, and weeks of planning. Once they arrived at their destination, vacationers would send holiday postcards to friends and family back home, featuring images of all the sights and activities they enjoyed.

Now these things are all but obsolete. Postcards have been replaced by social media outlets such as Facebook and Instagram. Lonely Planet, once the traveler’s bible, has been pushed aside by online booking sites like Expedia, Travelocity, and Makemytrip, which have effectively taken travel agencies out of equation altogether.

Sites like TripAdvisor and Priceline offer a plethora of travel advice and reviews of hotels, tours, and restaurants. Travelers can book flights online, access their boarding pass on their smartphone, check in for flights, and even go through automated clearance gates.

The travel industry, like many others, is being disrupted by great ideas powered by digital technology. Here are just a few digital innovations that have changed the way we travel:

  • Online booking sites like Expedia, Travelocity, MakeMyTrip, and Trivago
  • Wi-fi-enabled mobile optimization
  • Targeting and hyper-personalization using Big Data analytics
  • Digital discounts and traveler reviews on sites like Kayak and Tripadvisor
  • Smartphone apps to research vacation deals and check reviews
  • Wearable devices that manage payment, room keys, etc.
  • Bluetooth beacons that guide travelers at airports
  • Virtual reality that enable users to “tour” locations without leaving home

Travel companies are also using Big Data analytics to hyper-personalize the travel experience for customers. By collecting and analyzing each customer’s “digital footprint,” companies tap extensively networked digital properties and data collected via travel sites, social media channels, and other online sources to deliver content that fits the needs and preferences of individual customers.

Today’s consumers are trending toward spending money on memories and experiences instead of material possessions. Accordingly, travel companies are investing in digital storefronts and omnichannel approaches to keep today’s hyper-connected travelers snapping, sharing, researching, and reviewing on the fly – leaving immense data footprints for marketers to leverage.

For example, Bluesmart is a carry-on suitcase you can control from your smartphone. The app lets you lock and unlock it, weigh it, track its location, and alerts you if you leave it behind in your travels. Travel company Thomas Cook has introduced virtual-reality experiences across select stores. And Starwood Hotels has launched “Let’s Chat”, a feature that enables guests to communicate with front-desk associates via WhatsApp, Blackberry Messenger, or iMessage before or during their stay.

As the travel industry continues its journey from the oxcart to the hyperloop, the future will belong to those companies that use data-based intelligence to offer better a customer experience and build long-term loyalty.

For more insight on how advanced technology is affecting how we travel, see Connected Cars: IoT Disrupts The Once-Humble Automobile.

This article originally appeared on Simplified Analytics.

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Understanding Data: Gold Nuggets And Puzzle Pieces

Paul Lewis

I regularly use the colloquial phrase “nuggets of gold in a huge pot” when describing the value obtained from understanding and analyzing data.

It seems like an easy win. The phrase is well-known and highly digestible. Most people in the audience generally appreciate that gold has immense value, and there are whole industries that exist to mine this precious metal from a variety of mountains and streams. It’s also predictable that as you collect these precious nuggets, you won’t be able to carry them around given their collective weight, and a pot is as good as anything to store them. Plus, the whole leprechaun-esque vision it likely creates might bury the phrase in long-term memory for easy recall the next day with colleagues. Like, “I went to a seminar yesterday and this dude talked about value derived from analytics as being like nuggets of gold in a huge pot.” That’s helpful.

Occasionally, like here, I even blog about it. I find repetition to be tremendously valuable in retaining content. Additionally, I also find repetition to be tremendously valuable in retaining content. (Note: embedding subliminal messages in repetitive statements is also tremendously valuable, but I will get to that content later. Trust me, you won’t object.)

Unfortunately, as metaphors go, it’s extremely weak (especially considering pots are much more likely to hold coins versus nuggets.) Let me break it down so you see what I mean:

  • Data has value the instant it’s created, for as long as you hold it, until its demise
  • The final form of data could be deletion or decade-old archiving; the effect is the same
  • The value of data changes over time
  • Adding new data to existing data, more opportunity is created to discover a potentially endless series of value (Potentially)
  • This potential value could be expressed as an undetermined number of “nuggets of gold” (I guess, if you must)
  • The more data you have, the more nuggets of gold you could discover, and the more necessary a pot to hold them (That’s a stretch)
  • The more data you have, the more precise your statistical and mathematical models and more opportunity you will have to find more nuggets (Don’t buy it, sounds complex)

Getting the picture?

The fundamental problem with the metaphor is that I’m treating value-obtained as a direct representation of data-collected; i.e., you are storing various elements of a client, therefore hidden in one or more of elements is a single purposeful and valuable answer, hidden in the fields, row and columns:

  • Data, in the sense of a database, being a single field, in a single row, in a single column, is irrelevant. It carries no weight or value beyond the knowledge of collection. It lacks context and awareness. Whether static or variable, it tells no story and solves no problem.
  • Data, in the sense of unstructured data, bytes of binary information, carrys even less value. In fact, knowing that a single bit is only a small part of a greater whole, predetermines its unlikeliness to impact the entire picture.
  • Data, as a single point in time from a stream of information, is outdated the very nanosecond it’s used, as more current data takes its place, creating a new current reality.

The concept of “nuggets of gold,” by extension, then presumes a specific and direct answer to a question; or a direct and obvious correlation to an action:

  • How many toothpicks are in the container? 173
  • What color shirt matches best with my red pants? None, don’t wear red pants
  • What’s the name of that dude with the crazy beard in that class last year? For the last time HENRY!
  • If you were to spend $5 less, you would have an extra $5 in the bank
  • If we mix these two primary colors, you would have this one secondary
  • If I build more of this product, I will sell more of this product

Lesson learned: Individual elements of data possess little to no value

There is a reason why every company (including yours) has an enterprise information management (EIM) program and a chief data officer (CDO) responsible for stewardship of your most precious technological asset, data. As a reminder, EIM is an integrative discipline for structuring, describing, and governing information assets across organizational and technological boundaries to improve efficiency, promote transparency, and enable business insight. The program includes capabilities to store, protect, architect, manage risk and compliance, manage quality, classify, and organize data. A great EIM program focuses on how organizations derive insight and value from information, either from internal effectiveness and/or growth-oriented goals and activities.

A CDO, or VP of business intelligence, or manager of management information systems (MIS) understands that data, in its elemental form, does NOT equal value. They understand that value is derived from discovering patterns and appreciating the impact of change and time, and that data requires enrichment, not just discovery. The activity required to derive value is implemented in four capabilities:

  • Descriptive: MIS or reporting, focusing on hindsight (what has happened)
  • Diagnostic: Business intelligence or incident management, focusing on current-state insight or understanding “why” it happened
  • Predictive: Analytics combining models of previous data and application to new data, focusing on foresight (what will happen)
  • Prescriptive: Analytics and action, foresight algorithms to implement a business function

The EIM program also appreciates that the effort to create value focuses far less on finding a long-lost and specific piece of data, and instead focuses on studying patterns in static, changing, and moving information and researching correlations, causations, and theoretical application of mathematics and logic to create complex business value from data-centric components. Yes, it’s a science. It’s far less searching for a nugget of gold, and far more about determining that you could make money from gold jewelry… all from the same mine.

So here is my NEW metaphor

And for the sake of inconsistency, I’m not even going to use precious metals. Imagine a pile of random puzzle pieces. Each piece represents a single data point, collected from a variety of sources.

Before value can be obtained, preparatory activity is needed to curate and enrich data:

  • Extraction: Identify all the puzzle pieces in the house: under beds, in vacuum cleaners, in the dog bowl, etc. For data, discover all the sources of information: internally and externally, structured and unstructured, and classify.
  • Integration: Send out all the kids and parents to grab the pieces and bring them back to the pile. For data, connect to hundreds of sources for batch or real-time integration/ETL.
  • Enhancement and cleansing: Dust off each piece, glue back down the picture side, sharpen the edges, number the backs. For data, match and qualify, and add appropriate metadata.

This effort to convert raw data to content, and indescribable fields into describable objects, requires the capabilities of more than just a pile, a box of sorts.

A content platform (the box) allows organizations to bring together object storage (a place to put all data), data mobility (a means to abstract data from its sources), cloud gateways (ability to use multiple deployment models), and metadata (tagging and sophisticated search to create a tightly integrated, simple, and smart data intelligence solution.) You may have heard this being referred to as a “data lake.” I highly recommend this solution set, if you happen to be in the market.

For this new enhanced data set (puzzle pieces), contained in a content platform (puzzle box), the EIM value-creation activities can be described (it’s still the goal to find the Picasso):

  • Descriptive: Create a list of puzzle pieces, organized by shape/color/origin; determine which pieces closely resemble the palette of a master work of art
  • Diagnostic: visualize the current state of completing the puzzle; how far along is the process and/or discover missing pieces
  • Predictive: Given where we are in the process, and the remaining pieces still in the box, determine what picture we might be making and/or predict what might be the picture, even if we have missing pieces
  • Prescriptive: After having made dozens of pictures from these same puzzle pieces, guide the creation of existing and new completed puzzles

Both predictive and prescriptive analytics would use linear and non-linear algorithms (ways of thinking out the problem), would focus equally on the puzzle pieces that exist and the ones that are missing, and combine or use pieces from hundreds of potential sources to create hundreds of different works of art.

In a nutshell: The value obtained from understanding and analyzing data is not that you will find “nuggets of gold” of data or an individual puzzle piece that solves the problem. The value obtained from understanding and analyzing data is the millions of dollars in your bank account from building several masterpieces from all your individual puzzle pieces.

Learn how to derive more value from Data – The Hidden Treasure Inside Your Business.

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Paul Lewis

About Paul Lewis

Paul Lewis is the Chief Technology Officer in Hitachi for the Americas, responsible for the leading technology trend mastery and evangelism, client executive advocacy, and external delivery of the Hitachi vision and strategy especially related to digital transformation and social innovation. Additionally, Paul contributes to field enablement of data intelligence and analytics; interprets and translates complex technology trends including cloud, mobility, governance, and information management; and represents the Americas region in the Global Technology Office, the Hitachi LTD R&D division. In his role of trusted advisor to the CIO community, Paul’s explicit goal is to ensure clients’ problems are solved and opportunities realized. Paul can be found at his blog, on Twitter, and on LinkedIn.

The Future of Cybersecurity: Trust as Competitive Advantage

Justin Somaini and Dan Wellers

 

The cost of data breaches will reach US$2.1 trillion globally by 2019—nearly four times the cost in 2015.

Cyberattacks could cost up to $90 trillion in net global economic benefits by 2030 if cybersecurity doesn’t keep pace with growing threat levels.

Cyber insurance premiums could increase tenfold to $20 billion annually by 2025.

Cyberattacks are one of the top 10 global risks of highest concern for the next decade.


Companies are collaborating with a wider network of partners, embracing distributed systems, and meeting new demands for 24/7 operations.

But the bad guys are sharing intelligence, harnessing emerging technologies, and working round the clock as well—and companies are giving them plenty of weaknesses to exploit.

  • 33% of companies today are prepared to prevent a worst-case attack.
  • 25% treat cyber risk as a significant corporate risk.
  • 80% fail to assess their customers and suppliers for cyber risk.

The ROI of Zero Trust

Perimeter security will not be enough. As interconnectivity increases so will the adoption of zero-trust networks, which place controls around data assets and increases visibility into how they are used across the digital ecosystem.


A Layered Approach

Companies that embrace trust as a competitive advantage will build robust security on three core tenets:

  • Prevention: Evolving defensive strategies from security policies and educational approaches to access controls
  • Detection: Deploying effective systems for the timely detection and notification of intrusions
  • Reaction: Implementing incident response plans similar to those for other disaster recovery scenarios

They’ll build security into their digital ecosystems at three levels:

  1. Secure products. Security in all applications to protect data and transactions
  2. Secure operations. Hardened systems, patch management, security monitoring, end-to-end incident handling, and a comprehensive cloud-operations security framework
  3. Secure companies. A security-aware workforce, end-to-end physical security, and a thorough business continuity framework

Against Digital Armageddon

Experts warn that the worst-case scenario is a state of perpetual cybercrime and cyber warfare, vulnerable critical infrastructure, and trillions of dollars in losses. A collaborative approach will be critical to combatting this persistent global threat with implications not just for corporate and personal data but also strategy, supply chains, products, and physical operations.


Download the executive brief The Future of Cybersecurity: Trust as Competitive Advantage.


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Unleash The Digital Transformation

Kadamb Goswami

The world has changed. We’ve seen massive disruption on multiple fronts – business model disruption, cybercrime, new devices, and an app-centric world. Powerful networks are crucial to success in a mobile-first, cloud-first world that’s putting an ever-increasing increasing amount of data at our fingertips. With the Internet of Things (IoT) we can connect instrumented devices worldwide and use new data to transform business models and products.

Disruption

Disruption comes in many forms. It’s not big or scary, it’s just another way of describing change and evolution. In the ’80s it manifested as call centers. Then, as the digital landscape began to take shape, it was the Internet, cloud computing … now it’s artificial intelligence (AI).

Digital transformation

Digital transformation means different things to different companies, but in the end I believe it will be a simple salvation that will carry us forward. If you Bing (note I worked for Microsoft for 15 years before experiencing digital transformation from the lens of the outside world), digital transformation, it says it’s “the profound and accelerating transformation of business activities, processes, competencies, and models to fully leverage the changes and opportunities of digital technologies and their impact across society in a strategic and prioritized way.” (I’ll simplify that; keep reading.)

A lot of today’s digital transformation ideas are ripped straight from the scripts of sci-fi entertainment, whether you’re talking about the robotic assistants of 2001: A Space Odyssey or artificial intelligence in the Star Trek series. We’re forecasting our future with our imagination. So, let’s move on to why digital transformation is needed in our current world.

Business challenges

The basic challenges facing businesses today are the same as they’ve always been: engaging customers, empowering employees, optimizing operations, and reinventing the value offered to customers. However, what has changed is the unique convergence of three things:

  1. Increasing volumes of data, particularly driven by the digitization of “things” and heightened individual mobility and collaboration
  1. Advancements in data analytics and intelligence to draw actionable insight from the data
  1. Ubiquity of cloud computing, which puts this disruptive power in the hands of organizations of all sizes, increasing the pace of innovation and competition

Digital transformation in plain English

Hernan Marino, senior vice president, marketing, & global chief operating officer at SAP, explains digital transformation by giving specific industry examples to make it simpler.

Automobile manufacturing used to be the work of assembly lines, people working side-by-side literally piecing together, painting, and churning out vehicles. It transitioned to automation, reducing costs and marginalizing human error. That was a business transformation. Now, we are seeing companies like Tesla and BMW incorporate technology into their vehicles that essentially make them computers on wheels. Cameras. Sensors. GPS. Self-driving vehicles. Syncing your smartphone with your car.

The point here is that companies need to make the upfront investments in infrastructure to take advantage of digital transformation, and that upfront investment will pay dividends in the long run as technological innovations abound. It is our job to collaboratively work with our customers to understand what infrastructure changes need to be made to achieve and take advantage of digital transformation.

Harman gives electric companies as another example. Remember a few years ago, when you used to go outside your house and see the little power meter spinning as it recorded the kilowatts you use? Every month, the meter reader would show up in your yard, record your usage, and report back to the electric company.

Most electric companies then made a business transformation and installed smart meters – eliminating the cost of the meter reader and integrating most homes into a smart grid that gave customers access to their real-time information. Now, as renewable energy evolves and integrates more fully into our lives, these same electric companies that switched over to smart meters are going to make additional investments to be able to analyze the data and make more informed decisions that will benefit both the company and its customers.

That is digital transformation. Obviously, banks, healthcare, entertainment, trucking, and e-commerce all have different needs than auto manufacturers and electric companies. It is up to us – marketers and account managers promoting digital transformation – to identify those needs and help our clients make the digital transformation as seamlessly as possible.

Digital transformation is more than just a fancy buzzword, it is our present and our future. It is re-envisioning existing business models and embracing a different way of bringing together people, data, and processes to create more for their customers through systems of intelligence.

Learn more about what it means to be a digital business.

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About Goswami Kadamb

Kadamb is a Senior Program Manager at SAP where he is responsible for developing and executing strategic sales program with Concur SaaS portfolio. Prior to that he led several initiatives with Microsoft's Cloud & Enterprise business to enable Solution Sales & IaaS offerings.