But there is a growing consensus that data mining can help organization make better management decision. New book by Thomas H. Davenport titled “Analytics at Work: Smarter Decisions, Better Results” tries to provide some tips on how companies can take advantage of advances in analytics to improve business management (I have not completely read the book yet). They show how many types of analytical tools, from statistical analysis to qualitative measures like systematic behavior coding, can improve decisions about everything from what new product offering might interest customers to whether marketing dollars are being most effectively deployed. In their previous book “Competing on Analytics”, Thomas Davenport showed how pioneering firms were building their entire strategies around their analytical capabilities.
Data mining and analytics is new area and Mr. Davenport makes a compelling case for management to use data smartly to make strategic decision, I think depending on ‘data’ to make all the management decision is not wise. Remember how the new breed of data ‘guys’ at Wall Street were going to manage ‘risk’. Read last year’s Wired Magazine article titled “Recipe for Disaster: The Formula That Killed Wall Street” on how the Quants – brainy financial engineers- almost destroyed global banking system. This is also the gist of the book by Scott Patterson WSJ staff reporter titled “The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It”. See his interview on Bloomberg below.
Agreed, companies mentioned in the Economist article will not bring the entire economy down by thier reliance on data, but if they depend on the statistical data alone to make strategic decisions then there is a possibility that they may miss cues on macroeconomic impact, competitive threat etc. It’s OK to adjust the business strategy based on analytics but I don’t think companies should base their business strategy solely on the analytical data they are gathering.
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]]>“Real Time” data as marketed by BI vendors seldom mean subsecond or even subminute response. But there is increased latency from previous generation of BI tools. Low-latency BI, faster business activity monitoring, and ultra-low-latency complex event processing are all examples of stream processing technologies. They typically include instant alerts so people can react when a particular threshold, event, or pattern is seen. But at these speeds—anywhere from a few seconds for low-latency BI to milliseconds for complex even processing—most companies also need to couple low-latency insight with automated response. With software-as-a-service options, BI doesn’t always require the months-long distraction of building a data warehouse or a new data mart application, something particularly attractive for small IT shops.
See the survey result below which puts fast data exploration and ease of implementation as the top two priorities.
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]]>Doug Henschen author of this article writes why business intelligence initiatives continue to top CIO priorities, as executives demand better visibility of their organization. BI tools have often has fallen short of ideal, delivering insight into the past but not into up-to-the-moment performance or future prospects. That according to Doug is about to change.
Next-generation BI has four factors are driving it:
Predictive Analysis: 2007 bestseller ‘Competing On Analytics’, by Tom Davenport and Jeanne Harris, perked up the interest in companies to improve their profit by peering into the future. BI vendors that lacked analytic tools have rushed to integrate them into their BI suites.
Monitor And Analyze In Real Time: Faster business activity monitoring, and ultra-low-latency event processing is making BI ‘near real time’. Functionality typically include instant alerts so people can react when a particular threshold, event, or pattern is seen.
Commit To In-Memory: Much faster analysis now now viable because of in-memory calculations. In-memory tools can quickly slice and dice large data sets without resorting to summarized data, pre-built cubes, or IT-intensive database tuning.
SaaS: With easy deployment and upgrade SaaS promises to further alter the BI market by helping companies get these next-generation systems running more quickly.
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What is Googlenomics? Wired Magazine article by Steven Levy titled “Secret of Googlenomics: Data-Fueled Recipe Brews Profitablity” defines Googlenomics as dependency of Google on economic principles to hone what has become the search engine of choice for more than 60 percent of all Internet surfers, and then uses auction theory to grease the skids of its own operations. All these calculations require an army of math geeks, complex algorithms, and a sales force more comfortable with whiteboard markers than fairway irons.
Articles notes that Googlenomics comes in two flavors: macro and micro.
- The macroeconomic side involves some of the company’s altruistic behavior like giving away products like its browser, its apps, and the Android operating system for mobile phones. Anything that increases Internet use ultimately enriches Google.
- The microeconomics of Google is far more complex. It involves selling ads that generates not only profits; it also generates torrents of data about users’ tastes and habits. Google then sifts through data and processes in order to predict future consumer behavior, find ways to improve its products, and sell more ads.
Micro economic aspect of Googlenomics is not transparent to end users but it is the heart and soul of Googlenomics. With the data collected Google constantly performs self-analysis: a data-fueled feedback loop that defines not only Google’s future but the future of anyone who does business online. This is a classic use of Business Intelligence tool. Keyword and click rate are the bread and butter of Google. Google is using enhance BI to use that data to improve click rate.
In 2007 Thomas Davenport wrote a classic “Competing
on Analytics: The New Science of Winning” in which he argue that the frontier for using data to make decisions has shifted dramatically. According to Davenport the companies should use data-driven insights in building their competitive strategies. This in turn will generate impressive business results.
Google is that organization which is using Analytics: sophisticated quantitative and statistical analysis and predictive modeling to extend its competitive advantage. I only hope that Google does not put all its eggs in the basket of ‘analytics’. A new search model might emerge while they have their head deeply buried in the data. Google also needs to aggressively look at new ways to enhance search.
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When a company like Coca Cola, which has several flavored drinks wants to know what its customers prefer, what does it do? Well, it intends to use IT to monitor the pulse of its customers. According to Information Week article titled “Coke’s RFID-Based Dispensers Redefine Business Intelligence”, Coke plans to roll out the Freestyle drink dispenser nationwide which is taking the concept of customer choice to new heights, the most interesting aspect is the technology it’s built on. Freestyle will become Coke’s front-line robotic army for business intelligence, sending massive amounts of consumption data back to the beverage company’s Atlanta headquarters. The dispensers collect data on what customers are drinking and how much, and transmit that information each night over a private Verizon wireless network to Coke’s SAP data warehouse system in Atlanta.
Unique byproduct of this BI enabled dispenser is that Coke can try out new flavors and get back almost real time feedback on the viability of its success. It will no longer have to ensemble Customer focus group and try it out in a ‘lab’. The real world becomes the lab and the marketing department at Coke can watch consumers vote yea or nay on the viability of new product instantaneously. This not only improves the speed of feedback but also makes the entire test marketing process cheaper. The Information Week article notes that besides collecting data on what customers are drinking, Freestyle also lets Coke know what flavor cartridges each dispenser holds, so the company can advise outlets on when to order more. Coke also will use the wireless network to send out new drink formulas to the beverage machines with instructions on how to mix them up. And should the soda company ever need to recall a flavor cartridge, the network also lets it instantly disable dispensers across the nation. Coke research, product development, and marketing personnel worldwide can use that system to share information on successful regional product rollouts and marketing programs, so they can apply them in other regions. Globally, Coke offers about 3,000 beverages, and what works in one place is often tried in another with similar demographics.
Kudos to IT team at Coke setting this complex infrastructure so that marketing decisions can be based on analytical and statistical data. Not only that, this application streamlines distribution by automatically recognizing when to expect orders from the outlets. On top of that, global marketing departments can collaborate on their findings. This is a great example of how IT can recognize the company’s competitive advantage and automate the process to broaden the economic moat. Article also notes that Coke came up with the design themselves and are closely guarding the engineering details of the RFID based dispenser. With a competitive advantage like this, I think its a good idea Coke store its IT architecture details along with its recipe formula!
Also check out my other blog on Coke titled Emerging Role of IT in the Marketing Strategy of Coka Cola
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IBM, a premier computer hardware company, I think is known for reinventing itself successfully. First after being outsmarted by Microsoft in late1980s, IBM reinvented itself. Lot of people believed, IBM cannot survive. Read the details of the turnaround by the then CEO Louis Gerstner in his book titled ‘Who Says Elephants Can’t Dance? Inside IBM’s Historic Turnaround’. Under Gerstner’s leadership, IBM began to diversify into software and services, two ancillaries to computer hardware. IBM was then able to ride the internet wave along with the others computer makers in the historic dot com bubble of 2002. Since the bursting of dot com bubble, IBM has continued to globally diversify under the new CEO Sam Palmisano. IBM has since globally diversified itself and has continued to outgrow its competitors.
Now with the latest credit bubble, biggest drop in industrial production and productivity, future growth for IBM and other computer hardware companies is tough. Hardware is discretionary spending for most of the companies and this recession we have seen double digit drop in PC and Servers. But, IMB has continued to strategically reduce it exposure to hardware and have continued to diversifying into software and services. But that is not enough. IBM needs to reinvent itself again. Sam Palmisano in his letter to share holders for the year 2009, writes that ‘IBM believes that technology in the last two decades has made the planet smaller and flatter. In the next two decade we will see it become smarter – i.e. infusion of intelligence into the way the world works. Through pervasive instrumentation and interconnection entire society can be more productive, efficient and responsive.’
What is exciting is IBM has identified a growth area where it can extend its core competencies to carve out a niche to itself. IBM is focusing on the the need by people, government and nongovernmental organizations to create a sustainable global growth model to ‘smartly’ utilize existing resources with minimal waste. Here are the 7 areas IBM intends to focus on for the coming couple of decades
Smarter Traffic: smart traffic system encompasses tolling, embedding sensors and large scale simulation to predict traffic flow.
Smarter Grid: automated meter management system to tackle growing environmental concerns.
Smarter Health Care: to lower cost, reduce errors and empower patients
Smarter Food: tackle inefficiency and quality issues that plague the global food supply chain
Smarter Money: to enable a safer and more transparent global economy
Smarter Telecommunication: to develop next generation digital platform to enable people to join global economy
Smarter Oil: optimize oil well performance and protect the environment
I think, IBM, with its history in turnaround is well positioned long term to exploit these new trend in sustainability and Green IT.
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]]>Shirky, a prescient voice on the Internet’s effects, argues that emerging technologies enabling loose collaboration will change the way our society works. Interesting point Shirky points is how the institutions (I call traditional organizations) in their quest to maximize profits focus on the 80% of the market. This is where the long tail comes into the picture. Organizations cannot pursue last 20% of the demand curve because it’s not profitable. To get to last 20% market share, traditional organization acts as an inhibitor. But the Web 2.0 applications are creating infrastructure to collaborate can and will target the last 20% of the demand curve. Just look at Wikipedia. It has articles that Britannica would have never included in their encyclopedia.
Anyway, what Shirky points out is that institutions will continue to act as an inhibitor for the collaborative tools.
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]]>CRM tools can play a pivotal role to create 4 best practices to empower customer facing employees to achieve extraordinary, sustainable results. Attain real-world benefits such as:
Increased growth: With information at their finger tips, employees can cross sell products and services to the customers. CRM helps create repository of customer behavior at every touch point, thus helping organizations build a detailed virtual client model.
Enhanced productivity: With centralized access to all the customer specific data, CRM tools can enhance the productivity of the employees.
Achieve short-term goals: With the access to entire customer information, the management can align employee performance payment to achieve short term goals.
Improved collective thinking, flexibility and consistency: This is huge value added feature that the newer CRM tools bring to the organization. As they are Enterprise 2.0 enabled, they help build a community of customers. By enabling seamless feedback from the customers at the different touch points in the value chain, the CRM tools can convert a consumer to a ‘prosumer’. The collective knowledge can be harnessed to build a product or offer a service that will continually add value to the customers and increase the bottom line of the company. This also helps ever increasing fickle minded consumer to be more loyal to the brand since they are involved in shaping the product.
Check out Oracle sponsored white paper here
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]]>Here is the list from the article
New Media: The Internet has become the new media. What some call Web 2.0 is all around us in RSS feeds, blog posts and wikis from MindTouch and Socialtext, among others. All of these tools are inspiring new methods of corporate collaboration.
Social Software: Social networks such as Facebook and MySpace.com has shown us the way we can build a ‘virtual’ society. Enterprises are capitalizing on the success of social media and utilizing secure social software suites such as IBM Lotus Connections and business-centered microblogs such as Yammer and SocialCast.
Augmented Reality: Virtual reality like “Second Life” will blend with physical reality giving rise to augmented reality. For example, TC2 makes the Intellifit body scanner, a walk-in booth that does a 360-degree body scan to help fit clothes to people.
Information Transparency: There will be sensors everywhere. People will be able to “see” all their assets through tailored services such as personalized medicine. Google Health, Microsoft’s HealthVault and Revolution Health all aim to give users greater control over their health records online.
New Wave of Waves: Wireless technology with location-aware Web services and commerce will make dynamic digital spectrum replete with open access.
Platform Makeover: Virtualization, with software scaling exponentially on one machine to let operating systems multiply, has been steadily evolving. Cloud computing, in which users pay for computing infrastructure and applications from vendors hosting customer data on their servers and storage arrays, is also changing computing models.
Smart(er) World: Semantic technologies will enable computing devices to interpret patterns as humans do, via text, speech or situational means. Computers will learn and make reasoned recommendations and predictions, such as telling the user to wear a raincoat after a forecast of inclement weather.
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InformationWeek’s IT Olympics Weblog quotes some of the stats as shown below from the Paris base IT service company called Atos Origin that managed the IT infrastructure at Beijing Olympics.
- Systems in Beijing securely processed a more than 80% greater volume of data on competition for media and news agencies worldwide, compared with the Olympics in Athens.
- The IT infrastructure in Beijing enabled nearly 50% more stories to be published each day in English by the Olympic News Service, totaling an average of 500 stories each day during the Games.
- Atos Origin added 40% more sports disciplines to its Commentator Information System to provide broadcasters with more detailed, real-time information about more sporting events.
- IT supported about 30% more hits on the intranet for the Beijing Games, called INFO2008, averaging about 1.2 million hits each day.
- Systems collected and filtered more than 12 million information security events each day to protect against potential IT security threats. Of these, fewer than 100 were identified as real issues. All of these were resolved, according to Atos Origin, resulting in no impact on the Olympics.
In planning and managing a mega events like the Olympics, IT is going to play more and more central role. IT in the past could not be used because hardware was expensive. As IT hardware becomes cheaper and smaller, IT can successfully be used to ease the management of huge amount of data and information during a mega event. Also, maturing Business Intelligence (BI) tools can be used successfully to find bottleneck issues before they happen thus streamlining the event. The Web 2.0 technology which is built on a foundation of open collaboration and communication can also be successfully used to exploit collective intelligence of the crowd and fine tune the event to their changing taste.
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