To Byte or Not to Bite: The Myths, Realities, and Trends behind the Science of Big Data Analytics

Without data, a company would never survive in today’s global environment. With some data, it might have a fighting chance, depending upon the quality and timing of the information.  But what happens when a company has access to too much data, sometimes referred to as ‘Big Data’? Ironically, it too could go out of business even with the best technology and staff to manage it.  Why? …partly because the data’s ultimate value depends upon who interprets and communicates the recommendations to the rest of the company, a task often left to an internal employee or ‘Data Scientist’ who may be no more than a recent university graduate armed with theories and little industry practice.  

According to Dr. Jesse Harriot, the Chief Analytics Officer at Constant Contact and author of “Win with Advanced Business Analytics”, “setting up a data analytics initiative within a corporation is not a trivial endeavor”.  It requires a lot of sponsorship at the corporate level and can take a year or two before achieving a meaningful balance between the influx of web data and its collective value to the company. Harriot shared his wisdom at a recent conference in Boston titled, The Science of Marketing: Using Data & Analytics for Winning”. This power event organized by MITX, a Boston-based, non-profit trade association for the digital marketing and Internet business industry – (mitx.org), served up an impressive venue of expert panelists who shared their best practices and experiences.

Among them was a star performer, care.com, the largest online directory that connects those in need of care with care providers. Their co-founder and Chief Technology Officer, Dave Krupinski, discussed how the company uses analytics to drive all aspects of their marketing function including, attribution analyses, customer segmentation, user experience, and predictive analyses. As Krupinski explained to a packed room of 300+ professionals, “most CEOs blindly jump into ‘big data’ analytics expecting immediate returns, only to discover (and after great expense) the many intricacies required to get it right.”

Is ‘big data’ analytics really worth the trouble?

If economic times were healthier then maybe not, but with a slowing economy, companies are forced to either come up with the next differentiating product/service that will give them an extra edge over their competition or figure out better ways to surgically target likely buyers based on real-time data. But, increasingly, fickle-minded consumers whose loyalties remain largely unpredictable have made the task exceptionally challenging. …and yet, no one can blame consumers for their lack of brand loyalty when on average they are bombarded with over 500 ad messages per day.

A Typical Corporate Scenario
In a mocked up example for discussion purposes, a typical CEO hires a ‘Data Scientist’ or promotes someone from IT, after reading positive reports from companies that have boosted their sales using ‘big data’ analytics. Once budgets are allocated and a team is in place, software with funny names such as Hadoop, MapReduce, and HAWQ appear. These packages digest massive data sets (mostly unstructured data from the web) and respond quickly to complex SQL queries entered by a team operator or analyst. The output is then parsed into a more visual friendly format perhaps using expensive Business Intelligence (BI) software and when ready, shared at weekly management meetings. For this example, the meeting is adjourned without much warning. Management felt that the results from the Big Data Analytics Team were not aligned with corporate priorities, a common problem that points part of the blame on the Data Scientist’s poor understanding of managements business needs and on the CEO for not creating a comprehensive, formal data governance.

Disappointed CEOs tend to view ‘big data’ analytics as a ‘think-tank’ style department that delivers flawless dictates to the rest of the company, when in fact, ‘big data’ analytics should be a collaborative data-sharing effort among all departments.The secret of getting ‘big data’ analytics to work is less about massaging structured and unstructured data quickly behind closed doors and more about the timely reintegration of field data from every department to continually tweak predictions and outcomes.

What should a CEO do to encourage data sharing among departments?

Most department heads do not share their data with their cohorts either by choice or due to incompatibility issues.  To address this reluctance, a CEO should first explore a standardized database structure and data exchange format that would allow departments to share their data seamlessly. Next he or she should develop an incentive plan to encourage staff members to not only share their data but request data from others. The fewer restrictions imposed on inter-departmental data exchanges, the more likely, new ideas will blossom. Moreover, the positive behavioral changes in the workforce will help the data analytics team stay focused on corporate priorities. Keeping internal operations lubricated with both internal and external data analytics will boost a company’s revenues by default. This approach can lead to a passive revenue strategy that focuses more on balancing an operation guided by ‘big data’ analytics than relying on traditional consulting advice or CEO hunches.

A Five Stage Journey
I turned to a visiting professor at the Harvard Business School, Tom Davenport, to categorize the ‘big data’ analytics journey a CEO can expect to take. Davenport listed five progressive stages needed to achieve ‘big data’ competence in today’s business environment. First, there are the ‘Analytically Impaired Companies‘. These are companies that have some customer data but lack a centralized strategy to leverage its use.  Next up are the ‘Localized Analytics’. These entities outsource their data needs to companies that follow traditional marketing practices. Then come the ‘Analytical Aspiration’ types who centralize their data sources, enjoy C-level support, and operate an in-house data analytics team. At this level companies are just beginning to grapple with their ‘big data’ analytics issues. A fourth phase has been designated to ‘Analytical Companies’ who are showing some success in using data to drive their business. Finally, and at the top of the heap are the ‘Analytical Competitors’. These companies have fully integrated proven algorithms that combine unstructured web data, with reintegrate field data to seamlessly predict a specific customers expected wants and desires based on their personal past history with the company and elsewhere including the same for their closest peer group.

Most daunting to any CEO is the notion that companies ranked at Davenport’s ‘Analytical Competitors’ level can rely almost entirely on their algorithms to run their business. The indisputable outcomes dictate their level of ad spend per quarter, allocation of ads across multi-platforms, inventory levels per SKU, quality of maintenance support, head count, and so much more. At some point one might even ask what the role of management should be for a company ranked ‘Analytical Competitor’ and the talent/expertise needed to be an effective CEO in this soon-to-be, new normal.

© 2013 Tom Kadala

Speed Learning in the Workplace

Getting a college degree may help you land a great job but staying on the same payroll for a few years may depend upon how quickly you can keep up with changing demands and skill sets. With time at a premium, most employees cannot return to school nor pay for additional training.  To avoid layoffs and turnovers, company leaders are turning to social networking software solutions to help make their employees smarter, more resourceful and, hence, substantially more productive. How do they do it?  

With the human brain only capable of holding 5 bits of information at any one time, speed learning is less about personal assimilation of complex concepts and more on locating individuals within an organization with the required knowledge base.  If compared to a search engine such as Google, social networking would be the ultimate research experience.  Instead of having to query and search through a list of possible matches, social networking software helps the best solution locate the person making the query.  Promoted properly throughout an organization, the potential advantages and efficiencies to be gained using social networking software to solve problems or gain new insights, could be truly extraordinary.  Once more, anyone within an organization from an assistant to a senior manger are equally empowered to leverage the organization’s in-house expertise.  With these tools readily available, speed learning, as a means to an end, can actually be achievable, fun, and effective.

Unfortunately, there is one caveat.  The success of social networking software depends upon the level of penetration and adaptation at all levels within an organization.  If only one or two departments use the software, questions will go unanswered or the depth of expertise will become less effective.  To counter the inertia for change, software manufacturers include additional features for sharing web sites, photos, documents, videos, and processes.  Their designs deliberately appeal to the Facebook user so that people within an organization can find multiple reasons to interact or form communities and hence, increase the likelihood that important queries get seen.

In the case of Unisys, a worldwide information technology company with 15,000+ employees, their CEO. J. Edward Coleman, became an early adapter and role model for their social networking initiatives. Employees were encouraged to register their personal credentials at a ‘MY SITE’ web page so others could easily locate them based on their expertise. At another web page called ‘ASK ME’, employees could search for advice or guidance by simply typing in a question.  For sharing visions and goals, the company created a company-wide Advisory Council, which included regular comments from top management.

Speed learning is sustainable when workers perceive their organization as a reliable resource that they can tap on regularly.  Aside from a software solution, companies should also encourage internal chat groups (i.e. LinkedIn), podcasts from experts, wiki-style blogging sites, and regular lunch meetings with upper management.  At their venue of choice, workers can discuss issues, give meaning to data results, or test new ideas.  However, speed learning should not be limited to just within an organization.  When appropriate, outside consultants, suppliers, or customers should participate in a facilitated discussion process where strategic issues to improve efficiencies along a supply chain, for example, can be openly evaluated.

To ensure that each venue remains on target, a trainer, business coach or facilitator is recommended.  Their role is crucial to promote the service, monitor its progress, and ascertain that the learning process is constantly growing and improving in a progressive manner.

There are a number of social networking solution options to choose from.  Some packages favor one feature over others and should be evaluated to make sure they can meet intended requirements.  To help get you started, I have listed some of the most popular social networking software packages in use today.

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Yammer (www.yammer.com) – A free private social network for small and large companies, Yammer works great for people who have quick and brief questions that need prompt answers.  It is a secure package that can easily leverage the wide range of expertise and experience within an organization.

Jive (www.jivesoftware.com) – Considered by Gartner as the best-of-breed enterprise social networking solution that can be customized by in-house consultants. Jive offers both an internal solution for employees and an external one used sometimes referred to as Social CRM that monitors customer inputs from other social media outlets such as Twitter.  Not for everyone, Jive’s pricing is volume based.

Newsgator (www.newsgator.com) – A Microsoft SharePoint add-on, Newsgator makes SharePoint social.  It offers community sites based on projects, initiatives, and common interests.  SharePoint is Microsoft’s version of a collaboration enterprise package where workers can share web sites, manage documents, and publish reports.

Salesforce Chatter (www.salesforce.com/chatter) – Fully integrated with SalesForce.com, this package can help workers discover resources and ideas, connect with people and content, and collaborate with business processes in context.  If you already use SalesForce.com this package is a great way to incorporate social networking within your organization..

Social Text – (www.socialtext.com) – Operated by a group of young, dynamic, and ambitious programmers, SocialText.com offers the ability to create impromptu community spaces for online group communication and collaboration.  Their approach to social networking begins with familiar Facebook-like features that can be easily modified for business applications.

The Art of Social Media

Like barter, social media is one of the oldest forms of cultural exchanges where commerce and ideas have traveled freely from one person to another.  Why then, thousands of years later, has social media suddenly become the rage of our modern society?  How is social media evolving, today?

Newly minted buzz terms such as ‘hyperconnectivity’ point to a social media platform on steroids where endurance is measured by one’s ability to multi-task, multi-chat, and multi-exist for a claim to fame that is self-defined, self-awarded and in some cases, self-defeating (i.e. too many applications and not enough time in the day).  So what are companies doing today to successfully incorporate the ‘new social media’ into their next marketing campaigns?

At a recent Harvard-sponsored event on the future of marketing, called FutureM, experts from a wide range of companies shared their winning formulas and theories.  With the pride of a budding artist, well-known companies presented what they considered to be an optimal social media solution, one that subtly positioned their product message/brand during a consumer’s ‘social experiences’, for example, while chatting on Facebook. Company presenters agreed that the ultimate goal for today’s social media is to give customers critical tips, at the very moment they need them most.  Here are what some companies are doing.

Foursquare.com circumvents GPS regulations by allowing users to opt in and keep track of the whereabouts of their friends and families.  If a user agrees, they can friend a company, such as RadioShack, and regularly receive special coupons when passing an outlet.  Convenient and timely, the coupon is a time-sensitive display on a smartphone.  Another example is Audi.  Audi watches for major weather events to occur prior to triggering a Facebook question where they ask die-hard Audi customers how they survived the current storm or blizzard.  The outpouring of accolades and experiences quickly travel throughout Facebook every time readers click the ‘Like’ button, hence agreeing to share an unusually exciting Audi experience with their Facebook friends.  The viral buzz of how reliable an Audi performs in the worst weather conditions at the time everyone is experiencing bad weather is truly priceless.  Another example… Heineken has integrated a predictive game feature for soccer fans who can gain points every time they guess the next play correctly (ie. a corner kick).  Finally, devices such as the IPAD enable consumers to experience a brand or marketing campaign in entirely new ways. These experiences have become reasons for new conversations, interactions, and exchanges with people we know, some we do not and some that we simply invent.