In my recent interviews with IT services providers on the topic of innovation, one of the key findings was the many different ways in which innovation can be categorized. Some companies view innovation as simply an extension of their traditional R&D capabilities, others view their innovation as a way to prove their thought leadership, still others view innovation largely as a strategic marketing imperative. Sometimes, it’s a combination of these factors.
One interview that stood out was with Lem Lasher, the Chief Innovation Officer (and Global Business Services President) at CSC, who described to me a deep and holistic approach to transforming CSC’s innovation capabilities. Three things that stood out at me about Lem’s approach:
With Forrester’s new blogging platform in place, I have the opportunity to launch a series of blogs about tech economics. What do I mean by tech economics? To me, tech economics first means how the larger economy and the tech sector interact. I am interested both in how economic conditions impact the demand for technology goods and services and how business and government purchases of these tech goods and services affect the economy as a whole and the industries and firms in the economy. Second, tech economics is about the revenue of tech vendors, both what they are reporting in the present and past and what we expect those revenues will be based on future purchases by their business and government customers.
My published research on the US and global IT market outlook, industry, regional, and country IT purchase trends, big trends like Smart Computing, and the ePurchasing software market (which I also cover) will continue to be my platform for addressing tech economics. However, I want to use this blog to talk about four focused aspects of the tech market: 1) tech data sources; 2) tech industry definitions; 3) tech market developments; and 4) tech market dynamics. Let’s call these the 4Ds of tech economics, and each will have its own strand of comments and observations.
D1: Tech data sources will be of most use to the data geeks like me in tech vendors. These are folks who use my numbers in their own forecasts of the market for their firm and its products. These blogs will talk about the data sources that I use in building my tech market sizing and forecasts, issues and questions about these data sources, and how the data geeks can leverage them. I will share some (but not all!) of our secret sauce for our forecasts, and I hope you will share some of yours so we can all get better.
Sikka made two comments that indicate how he's thinking about the NetWeaver portfolio.
1. In response to my question about whether SAP is concerned that Oracle's ownership of Java will put it at a disadvantage, Sikka started by highlighting SAP's work on Java performance, but then noted the availability of good open-source Java software to support the requirements of SAP customers.
For the past couple of years, I have worked on the analysis of global banking platform deals at this time of the year. Currently, I’m again working on the results of a global banking platform deals survey, this time for the year 2009. Accenture and CSC did not participate in 2009, and former participants Fiserv and InfrasoftTech continued their absence from the survey, which started about two years ago. The 2009 survey began with confirmed submissions from a total of 19 banking platform vendors.
We would have been glad to see more participating vendors, in particular some of the more regionally oriented ones. However, US vendor Jack Henry & Associates as well as multiple regional vendors in Eastern Europe, Asia, and South America did not participate. Nevertheless, the survey saw some “newcomers” from the Americas, Europe, and the Middle East, for example, Top Systems in Uruguay, Eri Bancaire in Switzerland, and Path Solutions in Kuwait. Consequently, the survey now covers banking platform vendors in all regions of the world except Africa and Central America.
However, 19 was not the final vendor count: One of the 19 vendors, France-based banking platform vendor Viveo, dropped out of the survey because Temenos acquired it shortly before Viveo provided its data. Another vendor simply told us that it only saw business with existing clients and, in the absence of any business with new clients, it saw no sense in participating. While all other participating vendors won business with new clients (whether the rules of the game allowed Forrester to count that business or not), 2009 was not the best of times.
This post is the third in a three part series on Smart Cities. Best to start with Part I.
Two Approaches to Making Smart Cities
As with most things in life, there are a number of ways to approach smart cities. One way is to start from the ground up. A new city is born - a clean slate - to be made smart with the necessary infrastructure for its connected systems to communicate and collaborate to create an efficiently running city. A recent article in Fast Company, highlighted a number of smart cities projects that essentially started from the ground up - or, in one case, from the mud flats up. The most widely written about start-up city is Songdo. The concept was launched as a vision of the South Korean government and eventually, through the work of a real-estate developer and Cisco as the IT infrastructure provider, has become a reality - although the city is not expected to be complete until 2015. Songdo and other start-up cities have become one answer to the nagging concern about increasing urbanization.
Reconciling the rapid urbanization in China with the observation of one World Bank official that "Cities are expensive to retrofit and modify once they are built," start-up cities just might be one answer to China's urban needs.
This is the second in a three part series on Smart Cities. Best to start with Part I.
Urbanization in China Sets the Stage by Defining the Need
According to the World Bank, China's urban population was 191 million in 1980. By 2007, it was 594 million, excluding migrants. About half of China's population now lives in cities, and that trend looks likely to continue particularly as the government relaxes restrictions on internal movement institutionalized in the strict hukou system of residential registration.
And, bigger cities face bigger challenges to meet the needs of their burgeoning populations:
Infrastructure and jobs. Between now and 2025, it's likely that another 200 to 250 million people will migrate to China's cities, adding to an existing mobile or migrant population of about 155 million. Providing infrastructure - housing, roads, hospitals etc. - and jobs for this anticipated inflow of people poses major challenges. With new changes to the hukou system, this migration into cities could be even greater.
Energy. Urban residents use 3.6 times as much energy as rural residents; suggesting that energy use is far from its peak. In China, energy intensity (consumption of energy per unit of GDP) is 7 times that of Japan and 3.5 times that of the United States, and over 70% of electricity use is coal-produced.
This is actually not a tale of two specific cities but of two types of cities, or “smart cities” as the new moniker goes. It will appear in three parts.
Defining Smart Cities
“Smart” has become the adjective of choice among tech vendors to describe solutions that capture, synthesize and analyze the vast amounts of data being produced by computing and networking systems. Forrester defines Smart Computing as:
a new generation of integrated hardware, software, and network technologies that provide IT systems with real-time awareness of the real world and advanced analytics to help people make more intelligent decisions about alternatives and actions that will optimize business processes and business balance sheet results.
What does that mean in layman’s terms? Every system can be smarter if it can learn from and act on the data it produces.
A city is a “system of systems” making the potential for efficiency exponential as all of its systems interact. Therefore, a smart city is:
A city that uses technology to transform its core systems – city administration, education, healthcare, transportation, public safety, real estate, utilities and business — enabling them to capture, analyze and act on the data they produce.
As a result, a smart city’s systems can optimize the use of and return from largely finite resources. It can, in other words, “do more with less.” Using resources in this smarter way also boosts innovation, a key factor underpinning competitiveness and economic growth.
I recently published a sample business capability map for insurance firms as a way to illustrate many aspects about the description and use of this business architecture methodology. One of the readers of this report commented “It seems the business capability maps provide value as a complement to existing methodologies” and referenced Strategy Maps and Business Process Modeling. This made me realize that I should explain more how Forrester sees capability maps as more than a complement – and why we, along with many of our clients are so ‘jazzed up’ about this methodology.
A bit of background: Forrester views capabilities as stable elements of a business model, where the dynamics of a firm are reflected in the business goals for the capability, and the processes, functions, information and other assets which are how a capability is delivered. A capability map describes all the capabilities, and the relationships between them, which an organization needs to have as part of their business model to achieve outcomes. Think of Sales as a simple example, where there are business goals and associated metrics for Sales, and processes, functions, information and people assets necessary for this capability to be delivered. And Sales has a relationship to Fulfillment, to Customer Service and to Marketing.
Ever since I first started working with online social communities I've been thinking about just what it is that makes some communities successful while others fizzle and die. In particular I'm curious why collaboration communities seem to be so hard to make work.
While doing recent research on social computing initiatives I got to thinking on this problem again. Recently I made the connection to Abraham Maslow's work on the hierarchy of needs:
Maslow suggested all people are motivated by a desire to fulfill basic human needs in an ascending hierarchy. He also suggested that unless the lower-order needs are fulfilled, the higher-order needs are not motivators of behavior.
The primary needs Maslow identified fall into five groups: