This shows the effect of the two major industrial revolutions. The first one, in the 19th century was essentially based on manufacturing goods: it actually increased the GDP of “Western” economies considerably. Coal and steam were the main ingredients of this growth, as they allowed industries to move from unreliable sources of energy like wind and streams to a constantly available and reliable source. But it is nothing compared to the growth explosion of the 20th century, where GDP growth became exponential. The western societies moved from pure basic manufacturing of raw material to added value transformation manufacturing and services, again sustained by better source of energy: oil and nuclear.
4 countries – industrial revolution but exponential – flow of money buying stuff inside, investing in stuff – trade results
But if energy plays a capital role, technology made it possible. A closer look shows that the 20th century growth actually took place in the second half, and specifically since 1964, which is the introduction of the first viable mainframe (IBM 360) and the first symmetrical multiprocessor (GE600). If we correlate the GDP increase with investments in computing servers we get .97, which really shows that, if technology was not the cause of that spectacular growth, it was at least a major component of it. The question today is no longer to justify the role of technology in business growth, but whether that growth is sustainable and what role technology will play to make it so.
Growth happened in last part of the century – strongly correlated to computing – consumer oriented society – US 60% comes from consumers – computer was actually means to keep up with growth – organize the consumption of goods, produce goods faster, shifted from raw materials e.g. steel to sophisticated products – step in maturity was not possible without computing – computer supported it – 1983 – solutions not in terms of hardware – packaging ERP – next inflection is when we started talking about commodity hardware in beginning in 2000s
Can we continue to feed the monster – closer and closer to the customer - consumer
Business isn’t to support internal but to understand and get closer to customers – streamlining organization itself – better supporting the business e.g. CRM but supporting sales force and marketing – one step further – what is in the customer mind – what are they doing – what are they interested in – Kodak, Towers Record, borders, Blockbuster – didn’t listen to the customer – positive movement – Taxis – Uber – protesting – get information from customer – go to a to b – instant answer – know when will pick you up – not waiting – taxi has to buy a license – boston – medallion - $700K – renting to taxi’s $100/day – people who have limos or black sedans – 1904 Paris Taxis – over a century – didn’t change and now everything
Now services which are going to feed renewed business growth – smart – historical perspectives – very rick and very targeted – can target the individual customers – not looking at market segments – 50 mile radius – small car to do errands – apps that you can get from google maps, kindle reader, airline scheduling flights, phone to pay – fundamentally as a service that are free
Growing need to continue growing – changes face of it but the problem is money – IT budget mostly to support systems of record – previous generation – leaves little room for new projects
One had the system of records bunch of rusty fasteners but never use them that’s IT – grown organically but don’t even know what you have – system of engagement which is the new – how to reconcile them – everyone will have to face
Potentially 2 types of strategy – introduce economy of scale – intel processors, virtualization and further with cloud – rationalization of systems of records – wasting money on support – make new solutions cheaper, faster better by using commodity
As we need to move the goal posts of human ability, that is multiply our staff ability to handle production and maintain the quality of service, we have to turn towards what others have done in the past to resolve this issue. In the words of Charles Perrow, economy of scale, that is standardization of infrastructures and processes as well as adopting innovative technologies is the path towards a better productivity, that is a more rational use of time/task capabilities available in an IT Operation. Our strategy to fill the gap between human capabilities and the complexity of all the tasks that an IT Operation has to complete will be to: Reduce the diversity of infrastructures so that we can concentrate on fewer technologies and make a better use of time, Automate operations as much as possible to perform routine and repetitive tasks more quickly and efficiently, Abstract the remaining complexity through the use of operational tools that will provide a uniform layer over diverse technologies.
Forecast of cloud adoption – getting to 100% - based on data we collected in previous 4 years – economy of scale and instant gratification – need a server get it quickly – no forms no building no plugging in – create applications faster and be more product
Once we look at devops – economy of scale, faster releases- increasing complexity – one way to reduce is to put in place automation – abstract the complexity – different automation models – something for mainframe – on premise or cloud – abstract through automation
I&O are going to face a different structure – not going to build and operate we are going to procure and manage – once we put in place – what are the tasks that are left – service architecture – new tasks – infrastructure of code in service management and service architecture – software replacing not by touching hardware but using a software intermediary – using code to manage and design
We have a bunch of automation to put everywhere – manage individual tasks – all the automation are going to use the same infrastructure – will need to organize that – single user interface – structuring automation so it doesn’t collide with each other – living in harmony - coordinated
Emphasis on innovation and automation as well as the “industrial” production model.
Horizon 2020 - The Road to Converged Automation
Horizon 2020: The Road To
Amy DeMartine, Senior Analyst
The IT Pivot: Can We Reduce MOOSE?
Strategy to kill the MOOSE:
› Introduce economy of scale: standardization, cloud, etc..
› Rationalize and optimize systems of records
› Reconcile business and IT views.
“Productivity depends more on technological changes
and economy of scale than on human efforts.”
The New I&O Task Structure
Infrastructure and Operations are facing new challenges
….to architected automation
Conclusion: Embrace The Digital Disruption
› Think of IT management in terms of industrial disciplines.
• Innovate by introducing an industrial approach to IT operations
• Align IT with business objectives by first providing the ability to manage the “production line”
• Define management solutions strategies in line with this prime objective.
› Use automation as a way to revamp an existing production line.
• Automation provides reliability, repeatability and predictability to critical process execution
• Automation improves productivity by abstracting complexity and reducing waste. It embodies the "lean" industrial
› Leverage automation in the delivery of new apps and services.
• Automation increases speed, consistency and predictability when provisioning and deploying new business IT
Operability and automation will be the key words in the future data center: IT uses too
many resources to accomplish routine tasks that should be automated
Look for platforms, tools, and Apps that are standard, open, and cloud-based.
• Public cloud choices narrow to the big three versus everyone else,
• Heavyweight on-premises application life-cycle management tools fade as lightweight continuous delivery
• Software-as-a-service (SaaS) business apps pry the legacy application escape hatch open for progressive shops.
Scale Agile, Embrace DevOps, And Rationalize Portfolios To Accelerate Delivery.
• Leading firms are embracing DevOps to realize the Agile promise of faster delivery, while late majority firms work to
adopt Agile at enterprise scale.
• Rationalization processes have a new purpose -- identifying which groups of apps are suitable for replacement by
Expect To Pay More, Compete More For Key Skills.
• Cloud, mobile, and modern app delivery drive whole new skill sets that are in high demand, and therefore high cost.
• The legacy skills market tightens as baby boomers begin to retire in earnest in 2015.
• Expect to spend more on salaries, recruiting, retention, and training.