The dramatic growth in smartphone, tablet and vertical market portable devices e.g., medical instrumentation is starting to drive major change at big tech companies. If you watch product offerings and new positioning of Google, Microsoft, and Apple, you’ll see that significant investments are geared toward the mobile consumer and mobile information worker. These products require new device technologies such as flexible silicon and Thin flexible substrates for interconnect technology.
A good example of this is the lighting fast reorganization of Intel after Brian Krzanich’s installation as CEO. Under Otellini’s tenure Intel missed a huge opportunity to become the chip supplier to Apple for iPhones even though the traditional conservative “number crunching/data driven” advice given to Paul Otellini went against his gut, Intel passed on the opportunity. Their analysis misjudged the potential volume by a factor of 100 and over estimated the costs of manufacturing. Basically the conservative mindset of “group think” there projected the iPhone as a losing business proposition. See here The new CEO has immediately reorganized the global enterprise to make it more agile and created a New devices Group reporting directly to him. See here
Hopefully this will open Intel up to address new markets and new types of Si architecture along with manufacturing processes. Also the industry will hopefully follow Intel’s lead and innovate even more in this hot technology domain When you look at flexible silicon and thin film technologies, the future is clear. New companies will grow to tech giants that embrace this technology and benefit from lessons learned from the old tech giants.
The information age has brought about the rise of a new type of technology company. These are companies where the products or services they produce/provide are intrinsically connected to the IT infrastructure required to sustain the enterprise’s day to day operations. Unlike a food processor where the consumer product is supported by technology but disconnected once it is consumed. In these enterprises, the consumer buys a product/service that links them back into the enterprise’s IT infrastructure and the company monetizes this connection in order to perpetuate business and seduce the consumer down the path to purchasing more and more offerings to leverage the established link.
Even giants like Microsoft are going this way by eliminating free Hotmailand replacing it with free online Outlookand SkyDrivespace in the cloud. Companies who identify their current reliance on IT as a part of their business value proposition will be able to take advantage of this fact to create strategic inflection points. They will use adjunct offerings that take the enterprise to a new level of revenue and profitability. “Quick” tactical offerings with IT infrastructure “come-along” benefits will seed the prime rose path leading the consumer to partake in future offerings built upon a baseline infrastructure. Emergence of these new Technology Giants will be driven by executive leadership recognizing that IT isn’t just a necessary evil but rather an important platform allowing the launch of never before revenue models and opportunities.
The IaaS and PaaS cloud models allow architects to decouple components of an application or enterprise system into the lowest functional components and design for failure how these pieces can be utilized as “independent black boxes” to form an application. This allows for provisioning elasticity and resiliency of individual components and their states in the inevitable event of hardware or software failure.
One of the least understood impacts of this approach is that the message queues used by components can become the most important elements in assuring availability, scalability and ultimate reliability. In essence the messaging infrastructure components become the most critical parts of an applications infrastructure designed to exploit elasticity. If you envision these Enterprise Apps as complex organisms, then the message queues and their reliability become mission critical organs of the living, agile enterprise architecture. Components such as controller apps, databases and such should be isolated allowing buffering of request along with replies making the network of components more durable and state independent facilitating failover and scalability.
There are key information systems that can affect the health and profitability of an Auto enterprise over the next few years. This is because the issues of global economics, competition and the need for agility put auto companies in a position that require ultimate flexibility and agile JIT systems. Commodity pricing and cost sensitive third party components also stress an enterprise’s information systems forcing consolidation, analytics and visualization all be properly orchestrated in order to turn raw data into meaningful, accurate, actionable information. Market complexity is rising as is costing pressure putting the manufacturer in a “tight profitability corner”.
Some Requirements of Auto plant IT systems
Auto enterprises will need holistic information systems that all the formation of factories that are digital in nature allowing management to make quick decisions based on multiple views of data engaged as meaningful decision support information. Because consumers are enamored with technology, software controls for electronic components are making autos a complex of silicon components demanding overall systems software integration. These systems can impact:
Supply Chain Management (SCM)
If executed properly, good IT consulting can assist management to:
Speed the product design process,
Achieve faster time-to-production,
Enable increased manufacturing execution efficiency and production quality, and
Ease the management of design and production changes.
Manufacturing Execution Systems (MES) essentially use intelligence about the manufacturing process to monitor, automate and guide critical decisions of the digital auto factory. The ultimate goal is to utilize manufacturing informatics to increase the ability of operations to respond in an agile and effective manner to any situation.
In working at Intel and designing factory systems and management decision support systems we’ve learned many things that can apply directly to the auto factory. While working with the auto technology teams an Intel and Microsoft, we gained experience in how to integrate technology into the auto manufacturing process.
The influx of companies trying to exploit “Big Data” as a new revenue source has provided a number of workforce challenges for senior managers. Do they hire very smart math folk to devise new algorithms and create a “secret sauce” for their products? Do they develop or acquire superiors hardware that leverages new Si technology to better process big data? Do they form teams that have practical business experience to ferret out which real problems exist in the marketplace and what approach to analytics will be truly appreciated by customers’ end users?
Well the answer is … a little of each! The most important thing many companies are missing today is that they focus on the technology and technologist in their hiring decisions but not the business logic experience. There is great value in having teams of technology folk embedded with thought leadership coming from experience. Bright, eager, smart people, with minimal experience know theory and math but don’t know human behavior in business. They also don’t have the understanding of the technology assimilation hurdles that form huge barriers to rapid adoption and market share growth. The targeted customer base will often need help understanding:
How much data do we have?
What is actionable information contained in the big data fog?
How much information do we need to make decisions?
What changes in data are significant and require action?
What is a practical “on ramp” to use big data technology?
The bottom line is an integrated team of smart technologist stewarded through development with experienced thought leadership will result in the “BIG THEORY” required to make big data solutions palatable and easily digested by the human organism we call an enterprise. Where in reality, meaningful mobile visualization transforms BIG DATA into actionable information.