Data Center Automation

Operational efficiency and overall cost reduction are important factors in today's data center. However, as the world becomes more connected (vendors to customer, partners to each other, information workers to each other and so on), the ability to react with speed and flexibility is growing in importance.

Agile data centers will: manage the balance between speed and operational efficiency; understand their enterprise and its requirements; become agile where the enterprise requires it; measure agility improvements; and focus on agility through changes in technology, process and people.

Agility is the ability of an organization to sense environmental change and respond efficiently and effectively to that change. However, no organization will be agile if its data center and infrastructure aren't. Future infrastructure shared across customers, business units or applications, where business policies and service-level agreements drive dynamic and automatic optimization of the IT infrastructure, reducing costs while increasing agility and quality of service.

Speed and agility are not the same thing. Reacting with speed may solve a tactical problem, but it may also cause strategic efficiency issues (for example, the dot-com bubble followed by the bust). Speed and operational efficiency are often at odds with each other. An operationally efficient data center will standardize and eliminate exceptions; uncontrolled speed creates exceptions. Agility is the right strategic balance between speed and operational efficiency. Several metrics can be used to measure the “success” of the data center initiatives put in place by the data center managers.  These metrics can encompass broad initiatives in CPU utilization, storage utilization and human resource utilization. Since then, energy prices have continued to rise steadily, and awareness of both the financial and the environmental costs of enterprise computing has changed the way we view large data centers. As we retool IT to be better stewards of both enterprise and natural resources, greening our data centers, other measures should now come to the fore as well, based on data centers’ interfaces with the environment. The basic means of interaction are energy consumption and heat production.

Improving agility (to the level required by the enterprise) should be a measurable goal of an infrastructure strategy. The following initiatives can be key driving forces to form a successful strategy:

1. Standardization
2. Rationalization
3. Virtualization
4. Service-Based
5. Real-Time

Agility should be measured in a way that makes sense to the business — time and cost to deploy a new service, to roll out a new capability, to eliminate an old service or to react to changing business requirements. These kinds of measurements need buy-in from the enterprise as well as the IS organization. Within the data center, each of these business-related measurements should be broken down to internally meaningful measurements — for example, the time and cost to deploy new servers, to install new software or to fix a problem. This requires process definitions, process standardization, process measurements and monitoring, so that you can continuously improve processes and become more agile. Agility is not just about responding to change efficiently and with speed — it is also about sensing that change. From a speed perspective, the ultimate goal is to reduce the response time to near zero. The most efficient way to do that might be through an event-handling script, or it might be through effectively sensing precursor events before the event occurs. At the macro-level, this means staying in touch with the enterprise environment, for example, that a major sales event is about to take place, or that competitive pressure may change technology use. At a micro level, this means identifying precursor events (before a hardware failure, for example). Improving agility requires asking the questions: could this have been predicted, and what can I change next time to sense this kind of event before it occurs? Improving data center agility requires a combined effort in three areas: technology, process and people.

Technologies. Virtualization is a key technology in servers, storage and networking that gives the IS organization much more control over how resources are allocated. Automation and resource governance tools — and ultimately, service governance technologies — provide automated response capability to change (using virtualized resources effectively). There are a number of industry technology initiatives to improve the intelligence and self-management of IT (such as IBM's Autonomic Computing and On Demand, Hewlett-Packard's Adaptive Enterprise and Microsoft's Dynamic Systems). However, many of these technologies are still at the drawing board, or very immature, and will be evolving over the next 10 years. IS organizations should monitor technology developments closely, and use those technologies that can prove a rapid return on investment. Most importantly, having and maintaining a strategic plan for infrastructure technology is critical. Technologies are rapidly evolving, and successful IS organizations will ride the wave — they won't be left behind, and they won't crash ahead of the leading edge.

Processes. Operational frameworks like IT Infrastructure Library (ITIL) provide the backbone for operational efficiency. The starting point for IS organizations is process definitions and standardization. But an agile process culture is critical. Agility requires that processes be designed for change.

People. While technologies and processes can create the foundation for a more agile data center, ultimately it is the people, culture and organization that will make it work, and those that handle the more strategic and critical exceptions and events. Important factors include awareness of everyone's role in delivering agility to the enterprise, buy-in, feedback, career growth and involvement in the process. While operational efficiency is ultimately about cost reduction, agility is about increasing the value of IT, which should also mean increasing the value of IT personnel to the enterprise.

Therefore, agility is a critical success factor for data centers, and is becoming more important as agility grows as an overarching business requirement. Data center agility requires a successful balance between operational efficiency and speed — determined by business needs, and constantly evolving to deal with change. When considering agility, the following key points should be borne in mind:

1. Align with the business
2. Build a strategic plan that includes agility improvements
3. Measure agility improvements
4. Agility should be built into the IT architecture
5. Technologies are rapidly evolving
6. Processes must be agile
7. Don't forget the people side

SteelGlass with its strategic tool partners are helping IT organizations seamlessly integrate processes, people and tools to develop/optimize the business management group to ensure alignment of business drivers to technology drivers.

Business of Technology

IT Financial Management, a hot new area in addressing a key problem in companies with large IT organizations. IT organizations within non-IT companies view technology services as an afterthought and run those organizations without a strategy that is aligned in delivering business value and improving the bottom line that technology can deliver. Currently, decision making in IT organizations is made from disparate data sources that have misaligned allocation and recovery strategies.

A simple approach to help solving this key problem is to run the IT organization as a business through a collaborative and centralized approach to the “Business of Technology”. Past efforts in IT organizations to combat this problem has been through benchmarking, standardized metrics program, isolated business case development, business analysis after investment initiation, and a consumption view of costs. The result has been mixed with insignificant results. Benchmarking initiatives tend to lead to comparison of inconsistent models that are misaligned to business objectives. Standardized metrics program yield no actionable results due to data quality problems, such as, completeness, coverage and accuracy (CCA). Isolated business case development leads to subjective analysis geared towards a pre-determined agenda usually resulting in significant investment before detailed analysis. Lastly, consumption view of costs that is not consistent with the provider view of costs yields inconclusive data for highlighting the organizations inefficiency.

So the question is “how do we grow as an organization” and provide the key differentiator that IT can bring to the business’ bottom line?

Using the Greiner growth curve, large organizations are usually in Phase 4 – “Growth through Coordination and Monitoring”. This means that growth continues with the previously isolated business units re-organized into product groups or service practices. Investment finance is distributed and managed according to promise of future cost savings. Incentives are not recognized and there is a lack of alignment to corporate goals. Eventually, though, work becomes submerged under increasing amounts of bureaucracy, and growth may become stifled. This phase tends to end on a crisis situation where executive management wants to cut investment in IT.

A new culture and structure must be introduced by moving up the Greiner curve to Phase 5 – “Growth through Collaboration”. Companies that frequently challenge their organizations through change are best at recognizing the value of Phase 5. The formal controls of phases 2-4 are replaced by professional good sense as staff group and re-group flexibly in teams to deliver projects in a matrix structure supported by sophisticated information and financial systems and team-based financial rewards. Phase 5 ends with a crisis of “Internal Growth”. Further growth can only come by developing partnerships with complementary organizations.

Investment in IT

IT is reducing the amount of risk and uncertainty by aligning the real-time understanding of processes and organizational demands.Thus, IT  raises output per hour in the total economy principally by reducing hours worked on activities. Overall GDP increases....

But not all technologies, however, increase productivity by reducing the inputs necessary to produce existing products. Some new technologies bring about new goods and services with above average value added
per work hour. However, the newer technologies obviously can increase outputs or reduce inputs and, hence, increase productivity, if they are part of the capital investment plan.

The current factors of our economic landscape: 

• Revenue pressure on most sectors
• Current high fixed cost of IT in most companies is preventing economic agility to business revenue volatility
• Reduction of revenue in most sectors and the lack of IT economic agility, IT costs appear high relative to revenue which lends to targeted reductions --- leading a reduction in the IT budget
• Very few companies understand that currently is the best time to invest in IT (due to low borrowing costs) to lower overall operating expenses through increased automation and virtualization to increase margins
• IT still accounts for less than 10% of a company's operating expense which lends to the argument that there is 90% of expense that can be lowered

These factors combined have the potential to drive a new operational and economic model for IT that is agile enabling new levels of business value --- very few companies realize the power within their own organization.

SteelGlass through its 70 years of experience can help companies unlock the power within their organization by aligning people, process and technology through a programmatic approach...