Much our future as it unfolds relies on data. Whether it’s the evolution of digital twins or the ability of AI to aid in gene therapy, data is the engine. As the possibility space expands, so does the challenge associated with an overwhelming amount of data. The visual below via Visual Capitalist brings that scenario into focus using a connected car example. This related article highlights some of the potential obstacles. As with every scenario we envision, obstacles exist that slow or negate the scenario, while accelerants do the opposite. Envisioning possible futures requires us to understand both sides of this phenomenon – and doing so on a constant and iterative basis.Continue reading
IBM Report on Analytics
In October, IBM released a report from their Institute for Business Value titled Analytics – A Blueprint for Value. IBM releases these reports on a periodic basis, and this one is focused on the growing importance of analytics to business success. Through their analysis, they came up with nine levers that represent the sets of capabilities that most differentiated leaders exhibit:
- Culture: Availability and use of data and analytics within an organization
- Data: Structure and formality of the organization’s data governance process and the security of its data
- Expertise: Development of and access to data management and analytic skills and capabilities
- Funding: Financial rigor in the analytics funding process
- Measurement: Evaluating the impact on business outcomes
- Platform: Integrated capabilities delivered by hardware and software
- Source of value: Actions and decisions that generate results
- Sponsorship: Executive support and involvement
- Trust: Organizational confidence
MIT Big Data Panel Discussion
In May, I participated in a Big Data panel discussion at the 2013 MIT Sloan CIO Symposium. The panel was moderated by Tom Davenport, Harvard Professor and co-founder of the International Institute for Analytics. The panel participants aside from myself were:
- Annabelle Bexiga, CIO, TIAA-CREF
- Jack Norris, CMO, MapR
- Keith Collins, SVP, CIO & CTO, SAS Institute
- Michael Chui – Senior Fellow, Mckinsey Global Institute
This was a very good discussion on the potential of Big Data and the possible direction it takes in the future. Michael Chui did a great job with his opening remarks, referencing this Mckinsey Report and using examples from it. This report, which I have mentioned previously, focuses on major disruptive technology. It is interesting to hear the perspectives (and sometimes biases) of these industry players. It’s an hour and ten minutes long, with some very good audience questions.
Thoughts on 2013
Another year is coming to a close, and that means it’s time for 2013 predictions. Blog posts and articles will focus on the possibilities that lie ahead in the coming year. With so much uncertainty in the global community, people predict at their own peril. So this year, I am focusing my thoughts on the journey that I believe will dominate the rest of the decade. That journey will span three very broad categories: the accelerated movement towards systems of engagement, operating model change, and Digital innovation.
So here it goes – my thoughts for 2013:
IBM Big Data Study
The IBM Institute for Business Value recently completed Big Data research and released a report titled Analytics: The real-world use of Big Data. As the report states, companies have been dealing with large volumes of data for years (think billions of call center records collected by Telecommunication companies). But the report also identifies the two trends that make this era of big data different:
- The digitization of virtually “everything” now creates new types of large and real-time data across a broad range of industries. Much of this is non-standard data: for example, streaming, geospatial or sensor-generated data that does not fit neatly into traditional, structured, relational warehouses.
- Today’s advanced analytics technologies and techniques enable organizations to extract insights from data with previously unachievable levels of sophistication, speed and accuracy.
The Social Ecosystem
I recently viewed a video titled The Future of Social Inside the Enterprise, a thought leadership presentation from the recent Dreamforce 2012 conference. The presentation is delivered by Dion Hinchcliffe of the Dachis Group, and Alan Lepofsky at Constellation Research. This is a fifty minute journey through the past, present and future of social business. You’ll find some content on the business value associated with social, and some good examples of how social is evolving to support the way we work.
You can start to see how systems of record may integrate with systems of engagement. Two examples are given by Mr. Lepofsky. The first describes a stream level integration, which allows system of record events to be broadcast into the activity stream. This stream level interface is envisioned to be the place where people spend time doing their jobs. It is pointed out however that stream level integration has its issues, the biggest in my mind being the loss of context. Comments made in the activity stream do not work their way back to the system of record, so context is lost. The other critical issue is the noise level associated with these streams. Without robust intelligent filtering, these streams become worse than email. This filtering – finding the actionable insight among the noise – is critical to the effectiveness envisioned by future systems of engagement. I had a discussion this week with senior executives from a large Financial Services firm, and the general belief is that this critical filtering will take years to develop and optimize. It took IBM four years to tune IBM Watson to compete in the Jeopardy challenge. This is not simply a sentiment analysis exercise.
Big Data and the Emerging Era of Engagement
I often tell the IBM Watson story as a way of describing the future of analytics. Watson – with a large quantity of Big Data behind it – beat the two biggest Jeopardy winners of all time. Although that became the story, the bigger story for me was the business application of what I had just witnessed. Watson showed us how analytics will mature from descriptive to prescriptive. Most companies I talk to are still in the descriptive stage – reporting on that which has happened.
Is Data and Insight a New Source of Revenue?
In this world of Big Data and advanced analytics, many companies are starting to wonder about the revenue potential of their data. An opportunity to create new revenue streams is an attractive scenario – if data assets can become information products. Although not new, the number of companies that pursue information related products could grow considerably. Most companies upon inward reflection will find that the analytic core competence required to deliver insight – the higher end of the monetization scale – does not exist internally.
This introduces some interesting scenarios that underscore the market need for analytic outsourcing and the establishment of analytic centers of excellence. The evaluation process for this opportunity involves a market analysis that identifies the value-added information products for the target market. Understanding the business outcomes enabled by insight is a critical step in determining which products make sense. In addition, the data required to enable these products must be clearly understood, available, and clean enough to deliver the required insight. The process is then enabled by the appropriate analytic methods, taking advantage of advances in computing power and in-memory capabilities. The ability to include insight from unstructured data through the use of text mining expands the opportunity for value creation.
I envision a number of relationships emerging between technology companies and value chain players. These relationships enable new, more insightful information products by combining traditional data related skills with deep analytic and domain expertise. Companies will look to supplement existing offerings with analytic oriented products and services, or pursue new innovative offerings altogether. Insight as a driver of business and decision processes will be enabled in the future by internal movement towards analytic excellence, the use of external information products and services, or some combination of both. This is a natural response to the “Big Data” phenomena and the need to improve the speed and quality of decision making. It introduces a new era of information brokers that deliver new innovative products and services enabled by business analytics.
When Innovations Collide
The future of sustained competitive advantage hinges on the ability to effectively manage the collision of disruptive innovations. The digital disruption driven by Mobile, Social, Big Data, Cloud and the Consumerization of IT is impacting every industry. To date, much has been said about these individual areas of innovation. But the areas of intersection – critical to creating value from these innovations – have mostly been ignored. As innovations collide, the intersection must be effectively managed – or the result is distributed chaos. As the digital disruption takes hold across every company, in every industry, the need to transform becomes a business imperative – and future digital strategies will define success or failure.
Review of 2011 and Thoughts on 2012
2011 in my mind will be viewed as the launching point of a digital revolution. The momentum started in 2010 and kicked into overdrive in 2011. The rapid adoption of tablets and Smartphones fueled an aggressive development of mobile applications, while E-Book sales increased at a remarkable pace. Meanwhile, the world continued to go social in ways that few would have imagined. World leaders felt the power of Social Media, as revolutions expanded through the organizing power of Facebook and Twitter. Business leaders came to grips with the power of social media, as skepticism waned and social business turned the corner. Data continued to grow exponentially, expanding the gulf between available data and meaningful insight. Lastly, 2011 marked the year that cloud computing burst onto the enterprise landscape – In fact, 2011 may eventually be viewed as the year of the Cloud.
These factors combined to drive an aggressive digital expansion that in most cases happened through isolated initiatives driven by marketing. Businesses with indirect channels to market looked towards direct to consumer models. Regulated industries embraced the opportunity of social media, while addressing its risk. Customer experience became the mantra for many businesses, as re-inventing customer relationships topped most priority lists. New digital executive positions were created in response to growing questions about effective governance models. The notion of holistic digital strategies was in fashion again, and innovation and operating dexterity rounded out the top priorities for most executives in 2011.
Big Data and New Business Models
This recent Big Data Article from the Mckinsey Global Institute focuses on three key themes – some or all of which will impact every company in the future.
- Big Data will increasingly form the foundation of competitive advantage for years to come.
- Big Data will drive new business models across every industry.
- Decision processes will forever be changed.
A company’s use of Big Data will increasingly be driven by competitive pressures from those that effectively leverage its insight. As these companies mature in their use of data, they will shift from competitive response to competitive advantage. Decisions will improve, driven by an ability to simulate and model various scenarios that enable optimal outcomes.
The really interesting aspect of Big Data – and the analytics that help us derive insight – is the potential impact on complete value chains. This article provides some good examples of this phenomenon at work. In essence, data will drive new business models. Members of a value chain that own data may have an ability to monetize it. Those that have a proven ability to deliver insight from this data can monetize a core competence. Some companies may find themselves driving revenue from a business model that was never envisioned.
Whether it is new business models, better decisions, or enabled actions, the effective use of Big Data requires a level of analytic excellence that few companies have with any level of scale. This Mckinsey article echoes an earlier report that identifies a scarcity of analytic resources as a key obstacle to Big Data success. As I talk to companies about their digital strategies, I continue to focus on Big Data as the centerpiece of the strategy.
A New Kind of Intelligence
The explosion of data and content is not limited to social media and represents a top of mind issue for many companies. The opportunity exists to create unprecedented business value – but there are significant hurdles like greater risk exposure, more complicated risk management, and difficulty extracting relevant insight from large volumes of data.
As volume grows, automation is critical. For example, social media monitoring is a common practice today, one that becomes increasingly ineffective and costly as the social web expands. Monitoring tools that enable the analysis of dialog on social networks like LinkedIn, FaceBook and Twitter provide a basic level of insight. But a deeper level of insight still requires a manual process, where irrelevant content is filtered before finding meaningful insight. Information management is therefore a growing challenge.
From Social Listening to the Prescriptive Enterprise
I find myself talking a lot lately about the slow evolution from basic social listening to a more robust use of analytics to truly gain actionable business insight. I have long felt the evolution was inevitable – of course I often think these things and they take years to materialize – a story for a different day. This Recent Forrester Blog Post touches on the notion of moving from social listening, to integrating social and customer data. It also presents a roadmap for how to move through the crawl-walk-run-fly stages.
I am sure the authors realize that although this is a piece of the evolution, there are other steps along the path to actionable business insight. I’m already seeing the movement from basic social media monitoring to the broader use of text analytic platforms. Companies that started their journey focused on brand mentions are evolving to new use cases that deliver considerable business value. One of the signs that we are reaching an inflection point can be found in a growing move towards evaluating text analytics software for a broader set of use cases.
It Comes Down to Excellence
As I reflect upon a month full of customer discussion, it becomes clearer that future and sustained competitive advantage hinge on excellence in two critical areas: collaboration and analytics. The need for a relationship-based enterprise becomes more apparent as we look at the critical need to:
- Re-invent customer relationships
- Leverage the collective knowledge and talent of our organization
- Partner to facilitate operating dexterity
This relationship imperative makes collaboration excellence a critical success factor; and a key enabler is social computing. I don’t mean Facebook, Twitter, LinkedIn, or YouTube (although they play a role) but rather the use of social technologies to drive effective collaboration and communication. This evolution to social business moves the enterprise up the collaboration axis as described in the diagram below.
In a recent presentation, Forrester describes the uniqueness of our current business environment as a perfect storm of technology innovation. In the past, technology cycles were driven by one major innovation (mainframe computing, personal computing, networked computing). The current environment sees a perfect storm of cloud computing, social business, mobile computing, advanced analytics and smart computing. This latest cycle begins a period of accelerated innovation, and introduces a larger potential for disruption than in past cycles.
Disruption in many different forms is not just possible, but likely. Business models across many industries are already under attack. The Information Technology (IT) function itself will see considerable change over the next several years. As the workforce and business leaders play a bigger role in technology selection, the role of IT will evolve. What IT looks like in the future is anyone’s guess, but change is almost certain. The current outsourcing model that so many companies have embraced over the years, will change as cloud computing widens its footprint. The way companies build and deploy applications will change, as mobile apps and app stores shift from the consumer world to the enterprise. The way companies interact and communicate with all stakeholders will change, as social media evolves to social business.
Big Data is the latest buzzword attracting all kinds of attention. A Brand New Report by Mckinsey takes a detailed look at this new phenomenon. Mckinsey defines Big Data as datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze.