Big data can be monetized in three fundamental ways. These are each discussed below.
Big data can be used to improve operations, thereby reducing costs, improving efficiencies, ramping up sales, and increasing profits.
It can also be sold, licensed or shared with other organizations as a product.
It can be used to build a “multi-faceted” business, or even to launch new businesses.
The use of big data analtyics (BDA) is helping decision makers in dozens of industries. While it’s impractical to detail each one, the summaries below point out specific examples in key industries where BDA has taken a foothold and allowed businesses to extract monetary value by improving their operational efficiencies.
Manufacturers have used automation on the shop floor for decades. Today, companies are using big data produced by sensors built into manufacturing equipment to minimize outages through predictive maintenance. Such machine-produced data is expected to increase by more than 40 percent by 2020.
Healthcare operators can use BDA to map a patient’s data to the records of other patients, identifying patterns that can offer a more accurate diagnosis. BDA also helps prevent hospital readmissions that result from insufficient treatment on the initial admission, or from an incorrect initial diagnosis.
Commercial lending uses BDA to avoid risk by adding social media data to traditional risk assessment tools (credit reports, public data, etc.)
Energy companies have deployed smart meters in recent years and outfitted their distribution means (electrical transmission lines, pipelines, etc.) with sensors that give them near-instant awareness of problems. These advances reduce the cost of meter reading and of maintaining countless miles of distribution pumping stations and sub-stations.
The transportation industry has tapped big data from crowd-sourced data coming from mobile phone apps, and in some cases, from specially designed traffic monitors placed throughout a city.
While each industry uses big data differently, big data reveals more information, new information and new patterns of information that give insight that traditional warehoused data cannot. However, blending big data with traditional data stores adds context that allows better decision making. For example, the city of Boston maintains data on roads and highways that need repair. Citizens have long been able to report potholes and other obstructions via phone. The city decided its traditional phone reporting method could be enhanced with big data, so it created an Android app named “Street Bump.” The app uses the GPS and accelerometer in citizens’ phones to detect and report potholes and bumps that need attention. This crowd-sourced data is melded with existing operational data to facilitate road repairs, giving the city a richer and near real-time view of repairs needed on the city’s roads and highways. Combining existing data with big data adds the context that can impact budgeting, forecasting, and requirements for manpower and equipment.
Sell, License or Share Your Big Data
In choosing to monetize big data as a product you must give value to the buyer; it must be capable of revealing new information the buyer can can use to advance toward its business goals. It might help the buyer answer questions about risk, value of an asset or its future value. It might reveal insight into a market or customer behavior. But what gives a data product value? These are the essential ingredients:
The data may be high velocity, which means it is real-time or near real-time. Uber, the ride sharing company, gives customers the ability to find an available ride within a given radius, and tells the consumer how soon the ride will arrive. The Uber app used by customers and drivers handles both supply and demand in real time. It uses and produces high velocity data. From another direction, retailers often provide Wi-Fi in their stores so they can track the movement of patrons through the store based upon their smartphone signals.
The data product may offer greater precision than what is already available to the buyer. In today’s environment, large-scale digital systems such as mobile phone networks measure and record subscriber activity in great detail. Location, time of day, length of call and other facts become data as a subscriber moves through each day. Likewise, a web site visitor’s path through a site can be recorded in great detail. Similarly, a GPS tracking device like those often used by parents to monitor their novice teen drivers sends location, start/stop times, speed and other details to a server. Another example: Many web sites carry product reviews, however without appropriate safeguards, fake reviews can be posted to either bolster or disparage the product. Booking.com, for example, not only restricts reviews to people who are verifiable customers, it maintains quality control over each posting. As a welcome added feature, it also allows consumers to see reviews from their own demographic group: solo travelers, business travelers, families, etc. These are all examples of precise data.
It may offer greater scale. For instance, a data product that includes all data in a given population may have value to a buyer who, until now, has only been able to accumulate sampling data. A cellular operator such as Sprint or AT&T collects data with every phone call. A researcher seeking information on subscribers no longer has to work with a sample population of “N” subscribers. With all data collected, “N” becomes the entire universe of subscribers. There will be no sampling error because there’s no need to sample. The confidence interval climbs to 100 percent.
Another component one can add to the creation of a marketable data product is known as data fusion. Merging proprietary, internal data with public data or data from social media or another firm can create new insights. Data posted on Facebook and other social sites provides rich detail on a person’s interests, activities and preferences. This can be married with other data sets to create powerful new insights.
For example, Choice Point Precision Marketing (now LexisNexis Risk Solutions) maintained more than 17 billion records of individuals and businesses that scored cohorts on factors such as home ownership, a “prosperity index,” bankruptcies, Spanish-speaking and many others. Combining such information with social data, for example, can sharpen an advertiser’s focus immeasurably.
Launch a New Business
Perhaps the company that has made launching new businesses part of its DNA more visibly than anyone else is Google. (Their formation of Alphabet, Inc. as its parent company attests to the diverse interests Google has pursued). This blog post announcing Google.org’s influenza tracking initiative shows how collecting massive amounts of big data can be used to solve real world problems.
While this free service is no longer operating, it could have become a standalone business selling data. Instead, Google became a major contributor to Calico Labs “whose mission is to harness advanced technologies to increase our understanding of the biology that controls lifespan.” Staffed by scientists, Calico intends to find interventions to slow aging and counteract age-related diseases.
Build a Multi-Faceted Business
Amazon, too, has collected mountains of big data on millions of book sales. With a view into the book selling business, they launched their Kindle reader product and encouraged writers around the world to self-publish their fiction and non-fiction in Kindle format. More recently, Amazon launched ACX.com. It is “a marketplace where professional authors, agents, publishers, and other rights holders can post fallow audio book rights. At ACX, those unused audio rights will be matched with narrators, engineers, recording studios, and other producers capable of producing a finished audio book, as well as with audio book publishers.”
Not missing a beat, Amazon bought Audible.com and encourages authors to publish their audio books through Audible to earn premium commissions and royalties. Along the way, Amazon also launched WriteOn, a site where aspiring writers can post their work and receive advice from peers. Amazon seems to have wrapped most of the writing, publishing and book selling business into these various business units. In the process it has become a model of the multi-faceted business. And all of this has been driven by creative thinking salted with big data.
For companies that have accumulated substantial volumes of big data, it may sometimes be possible to “flip” the relationships that exist to create a new data product.
Consider how the Amazon Prime Video service keeps track of what you watch, what devices you register (TV, phone, computer, etc.), and then makes recommendations on what else you might enjoy watching. Such “recommendation engines” are widely used at music streaming sites, at Netflix and other ecommerce sites. They help subscribers discover new products and encourage additional sales.
However, when viewing preferences are combined with subscriber information, and further combined with demographic and economic information gleaned from list management companies, social media and other sources, the big data can be “flipped” to reveal new, marketable information.
For example, the subscriber’s home address serves as a data point that speaks to his or her income level. A service like Amazon Prime Video could identify subscribers according to their income cohort, then segment each cohort by their preferences in movies. Changing the view of that big data, “flipping it,” so to speak, gives a new view—and a new data product—that may be of interest to movie studios, producers and screenwriters.
If you’re seeking ways to harness big data — or any other disruptive technology — to deliver business breakthroughs, or even just for incremental competitive edge in your business, WGroup’s principals can help. Visithttp://thinkwgroup.com/why-wgroup/#/point-of-viewfor our unique take on rethinking IT. Or, if you’re facing pressure to transform your business right now, contact us for a consultation. There’s no obligation and you’re sure to derive at least some value from the conversation! Click here to get started.
Big data is well understood, at least in a general sense. But it’s worthwhile to note that it can include content from a wide variety of sources. Among these: content from internal company data warehouses, social media, click stream information from the company’s websites, the content of customer emails, customer online product reviews, survey responses, details of mobile phone call records, photos, videos, SMS texts, transaction data, and data produced by “Internet of Things” sensors.
SAS estimates the amount of information stored worldwide totals 2.8 zettabytes (2.8 trillion gigabytes) today, and will grow by a factor of fifty by 2020. Data centers across the planet now occupy some twenty-five square miles, equivalent to the entire land area of Syracuse, NY,  home to over a million people.
Three key trends in big data deserve your attention as gathering business intelligence from big data continues to unfold.
First, big data is derived from previously untapped sources. All these new sources of “in the moment” data can be melded with historical data to allow predictions of what is most likely to happen in the future. With appropriate predictive analytics tools, analytics becomes much more than a look at “what’s already happened.” It gives one the ability to predict what will happen next. This convergence of historical data and “now” data is what companies need to make business decisions aimed at growing profitability.
Second, there is a need for automation technology. With data flowing into an enterprise from so many directions, automation is a baseline requirement. Machines are well equipped to process huge volumes of information. People, not as well. The sheer volume, velocity and variety of big data you might choose to evaluate far outstrips a human’s ability to process.
Third, getting value from big data calls for flexible, less fragile, more adaptable systems. You might have built data stores that, after much planning, debate and discussion, specify particular formats for the data to be saved in various databases. Big data cannot be processed by systems that require information to be stored with rigid schema that need re-engineering every time a new source of data appears. Instead, analysis of big data requires you build a processing infrastructure that’s flexible and adaptable.
 http://www.sas.com/en_us/insights/analytics/big-data-analytics.html (from the video)
Digital transformation isn’t just about new technology; it’s about re-envisioning the organization as a whole. That means ensuring that the workforce is up to the task of making digital an integral part of their work life and using it to improve the business on a day-to-day basis. This doesn’t just include the IT department, but every single worker in the company. Business leaders must engage with their team and help them build the skill set necessary to succeed in the digital enterprise.
Identify deficiencies – Does the team have a product mindset and are they exceptional at collaboration, communication, problem solving, learning and troubleshooting? The most effective digital workers understand technology, how it can be used to improve the business, and are comfortable working and learning with it every day. Attempt to find areas in which team members may be lacking, and use that information to build a strategy going forward.
Train and hire – If there are areas in which the workforce is lacking, it may be necessary to make adjustments. This might include investing the necessary resources to equip staff with the skills required to harness the digital transformation. It may also require hiring new professionals to implement and execute the digital-transformation strategy.
2. Develop a digital-transformation strategy and roadmap
Undergoing digital transformation requires careful planning and deliberate execution. It is important for business leaders to be aware of both the potential opportunities and risks of implementing the strategy. This involves working with key stakeholders in the company, both on the IT and business sides, to develop a plan that meets the needs of the entire organization and end users.
An effective digital-transformation strategy:
Considers the business opportunities and aligns to the business strategic plan
Educates and communicates the changes required of all stakeholders
Pilots automation and cognitive solutions with clear success metrics
Aligns ITSM processes to account for multi-speed IT
3. Data management and governance
Data is the fabric that binds the components of digital DNA together, and good data governance is one of the core tenets of an effective digital enterprise. This should include the specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archiving, and deletion of data and information. It should also include the processes, roles, standards, and metrics that ensure the effective and efficient use of data and information in enabling an organization to achieve its goals. This provides a solid foundation on which to build a digital enterprise that uses data to make it more efficient, profitable, and competitive.
4. Relationship management
As third-party services rapidly become more important and zero-footprint IT becomes a reality, relationships become increasingly important to the digital enterprise. Relationship management spans IT, vendors, and customers; it forms the foundation of effective long-lasting partnerships. It’s critical that business leaders set clear expectations for those they work with and maintain complete transparency. That means holding vendors accountable to their SLAs and ensuring that they are actually meeting the real needs of the business and the end users.
5. Engagement model with the business
Digital DNA must be an integral part of the business and should be fully engaged with it. The digital enterprise must have technology embedded in the lines of business with a reporting structure both to the business head and the CIO. This ensures accountability and that the core focus is always on driving business goals.
Establish product owners – Each piece of the Digital DNA – including systems of insight, intelligence, engagement, protection, and record – must have a designated product owner. These product owners are accountable for both the outcomes and capabilities of their respective components. This is a very different way of thinking about traditional IT. Outcomes and capabilities foster a mindset of value – value to the business, customers, partners and shareholders.
6. Quality management
The digital enterprise is complicated and multifaceted. It is extremely important that the business leaders take steps to ensure every component is working properly and delivering the expected business results. This means conducting end-to-end testing as part of doing business. Each digital DNA component will be moving at a different velocity, and ensuring all the components work properly needs to become a core part of the company’s mission.
Disruptive trends are besetting the traditional IT organization across corporate America: Shift of IT decisions to business units, convergence of IT and business process outsourcing, cloud, social and mobile computing, and the consumerization of technology all conspire to demand a rethinking of the role of IT and of the CIO itself. There is urgency to act.
As the breadth of new technologies being developed and disruptive trends increase exponentially, it can be challenging for companies to understand these changes and how to adapt to them. At the heart of an effective digital enterprise are several key components that allow the company to leverage cutting-edge technologies and processes to drive business outcomes. Understanding this framework and how to successfully refine it to the needs of the company is key to achieving success in the digital era.
Systems of record
A company’s systems of record include core business transaction systems, including ERP systems (finance, HR, payroll, CRM, materials management, inventory, supply chain, and distribution) and record-keeping systems (financial services, healthcare, and all insurance verticals). These systems of record maintain and provide access to the key information businesses need for compliance, accounting, supply chains, and strategic planning.
The rise of information governance and MDM – As technology systems develop and IT processes adapt to be more business-focused, information governance and master data management (MDM) are becoming increasingly important. Paper records are rapidly becoming a thing of the distant past, and companies are looking for new ways to maintain and improve the accuracy and accessibility of their information. Data holds all of the digital DNA components together, yet most organizations don’t invest enough in master data management and data governance to allow the ecosystem of digital systems to interact seamlessly. This means taking new, holistic approaches that seek to address issues relating to compliance, organization, access, and retrieval. Implementing a comprehensive information-governance program supplemented by MDM can help ensure that the company’s systems of record are effective, accurate, and accessible.
How fast these systems can change – Because the data maintained on systems of record can be extremely sensitive and valuable, transitions to new technologies require care. Changes are often complex and time intensive. Business leaders should be cautious when implementing new systems of record to ensure that they will deliver the level of accuracy necessary. The release cycles for most companies will usually not exceed three a year.
Systems of engagement
Whether they be customers, employees, or partners, human beings are the driving force of every company. Systems of engagement are the interface between technology and humanity, connecting your team with business leaders, colleagues, and customers worldwide. Systems of engagement include mobile applications, SaaS tools, wearables and a wide range of other new technologies that have allowed businesses to engage more effectively.
The Cloud and mobility – Web and mobile applications facilitate interactions by allowing companies to quickly and easily reach out to customers and communicate internally. Recent statistics show that more than 10 apps are downloaded each year for every human being on the planet. Apps like Uber have already disrupted countless industries, while new technologies and innovations are likely to disrupt many more.
Similarly, SaaS applications have revolutionized sharing and collaborating internally and with partners worldwide. This makes it easier for companies to expand into new markets and source better talent, while still maintaining close, constant contact across offices.
How fast these systems can change – Systems of engagement can change much more rapidly than systems of record. Companies can easily add functionality because most of the systems rely on web or micro services, allowing companies to deliver new capabilities in as little as two or three weeks.
Systems of intelligence
At the cutting edge of digital technology are systems of intelligence. These systems include the automation, cognitive computing, smart sensors, and cloud solutions that allow companies to drive efficiencies, predictability, and accuracy across the enterprise. They represent some of the most exciting and potentially disruptive changes in the digital enterprise, but they are also the least developed.
Automation and cognitive computing – Automation is a human-productivity multiplier. It takes many of the time-consuming, repetitive, and error-prone tasks traditionally done by human workers, and allows them to be done faster and more accurately by machines. This includes simple customer service interactions, the basic assembly of manufactured goods, and the automatic repair of IT systems and services. This list will only continue to grow in coming years, as a greater number of tasks are able to be done by computers more accurately and with greater efficiency.
IoT – Systems of intelligence often extend into the realm of IoT (Internet of Things), collecting, analyzing, and acting on information and interactions that devices have in the real world. This can have significant implications for business, as companies can develop new business models and improve existing ones through more effective manufacturing, monitoring, and customer interactions.
How fast these systems can change – Although automation and cognitive computing are relatively nascent technologies, they can provide value to companies today. However, it is important for the organization to be mindful of how implementing automation technology will impact the company, its customers, and its employees. It is often necessary to gradually shift employees away from smaller tasks such as IT tickets, with automation tools acting as a supplement to the human worker, rather than a replacement. As these systems become more robust, it is likely that they will continue to allow companies to make greater improvements to their efficiency, customer service, and profitability, as well as provide an alternative for outsourcing.
Systems of insight
Systems of Insight are the tools companies need to better understand customers, optimize their operating model, and gain a competitive advantage. IoT smart sensors and applications collect data, while effective business intelligence and analytics allow companies to make better, more informed decisions.
Business intelligence and analytics – Having the right information at the right time is one of the most important elements of effective business. However, it is important to remember that it’s not enough simply to collect data. The key to powerful business intelligence is collecting the right data and extracting the most value from it. New technologies have made it easier to collect massive amounts of data, but data analysis has been relatively slow to catch up. With new innovations and better insight strategy, companies can more easily locate the most valuable insights and more effectively use them to drive business goals.
Data lakes – Data lakes provide organization-wide data management built to allow users to manipulate and analyze data across many formats and applications. This brings the power of Big Data into more areas of the company, potentially helping to improve efficiency and productivity across the enterprise. However, just because data lakes allow for easier access to data doesn’t mean that everyone within the company will have the motive or know-how to use them. This is an area in which it’s critical to ensure the required talent and training is in place before implementation.
IoT – Network connected devices also can play a significant role in a company’s insight infrastructure. By collecting real world data in areas like manufacturing lines, vehicles, and storefronts, companies can increase efficiency, reduce problems, and better meet customers’ needs.
Systems of protection
As a company undergoes a digital transformation, it becomes increasingly important that its digital assets be well-protected. Hiring key talent and investing in robust systems of protection is critical to avoiding breaches, downtime, or other damaging problems. Companies are being built on digital systems and cannot afford to have their very foundation exposed.
Proactive and defensive information security – Information security is one of the most critical elements of a risk-management strategy. Most companies are content to simply implement defensive information security systems. These might include firewalls, anti-virus software, and staff on hand to respond to breaches. However, for the digital enterprise, this is simply not enough. Companies should be proactive in their efforts to improve the security of their IT systems. This means hiring third parties to conduct full penetration testing, engaging with industry groups to identify and respond to threats, and building more robust systems of security.
Risk management – A company’s information security efforts should only be part of a broader risk-management strategy. This includes implementing systems of data backup, having offsite workplaces, and other solutions to mitigate the overall risk to their IT systems.
One of the most important considerations when adopting new cloud technology is cost. By taking steps to ensure that your organization is implementing the cloud in a way that provides a high ratio of benefits to costs, the organization can help make IT a revenue enabler that adds value to the organization.
Make a cost/benefit analysis – Whether your organization is implementing the cloud for the first time or evaluating current deployments, a good first step is making a cost/benefit analysis of the technology. How much will upfront and monthly costs be for the cloud deployment? How much will the company save in productivity, increased sales, or reduced downtime? What are the costs of alternative solutions? The answers should inform any cloud-implementation decision.
Repurpose existing investments – One of the most effective ways to reduce the cost of the cloud is to repurpose existing investments as entry points. By using an enterprise technology framework to identify what can be reused and what needs to be rebuilt, organizations can greatly decrease the financial costs of a cloud deployment. Investments made for server consolidation, ITSM, virtualization, API adoption and development, high availability improvements, and scripting automations are examples of improvements that can be applied to private-cloud deployments. They also can be a part of a hybrid deployment or integrated into a public deployment.
Negotiate agreeable terms – When working with public-cloud vendors or MSPs, it is extremely important to negotiate terms that meet the needs of the organization. Make sure that your organization has considered what maintenance is included, what the uptime guarantees are, how much support is available, and the vendor’s reliability record. They will all influence the ongoing cost of the deployment.
Evolving your cloud implementation
To ensure that your organization stays competitive and takes full advantage of the growing power of cloud, it is important to constantly evolve your cloud implementation. Below are some key questions and steps to help your organization make its use of cloud more effective.
Identify the business challenges our organization is facing.
How is IT affecting these challenges?
How effective are my cloud implementations (if any)?
How are our business stakeholders interfacing with cloud vendors without us?
What are the existing investments that can be repurposed as entry points to the cloud?
How will our internal cloud capability grow alongside our virtualized environments?
How will we start building relationships with external cloud providers?
As we begin to adopt more cloud solutions, how will it change our network architecture and data center requirements?
What cloud deployment models can be used to fill gaps, improve efficiency, and build the business?
Are the internal cloud and external environment more efficient and cost-effective?
How will we maintain talent?
How will we manage current providers and continue to build relationships with new ones?
Do we have systems in place to help us keep pace with changing technology?
How will the cloud impact how we interface with our suppliers and our customers and deliver our services?
What are the opportunities for reduced costs?
What are the opportunities for improved efficiency?
What new means of charging and paying for services does the cloud allow?
How can the cloud help our organization drive profits?
How will the cloud affect IT’s ongoing budget?
How will the cloud affect IT’s capital and operational expenditures?
New operating models
How do we manage security in the public and private cloud?
What are the greatest threats to a cloud deployment?
How do we ensure performance?
Do existing SLAs ensure uptime?
What staff do we need to maintain? What skills do they need?
How does the cloud affect enterprise architecture?
How does the cloud affect governance?
Are you looking for expert assistance in driving your cloud strategy to higher levels? WGroup’s cloud strategy consulting services could be exactly what you need. Learn more at http://thinkwgroup.com/services/cloud-strategy/.