Oren’s Weblog

The Ziff Davis folks have a story showing some of the enhancements in the latest build of Vista, Microsoft’s next version of Windows.

While I’m sure all of the new security and stability features are the real reason you should think about upgrading when this becomes a production release of Windows (MS says late 2006), I think this new volume control, which allows you to adjust the volume of sound from different applications independently, is a terrific enhancement to Windows:

Bridging the GAP: Unified Approaches to Governance, Architecture and Procurement

Jonathan Murray is VP and CTO of Microsoft for Europe, Middle East, and Africa. This is a new role for the corporation. He runs a group of 30 technology officers around the world that work with government, educators, and others on policy implications of technology.

The World Bank today spends about $1 billion a year on ICT related projects. Sixty percent of those projects have been failing, which has major implications on emerging markets. Jonathan had worked as a technology officer at ARCO before coming to Microsoft, so had a background in enterprise scale IT issues. An example is Siemens, which has 350,000 desktops in 120 countries – highly complex environments. At Microsoft he put in measures to gather data on customer satisfaction with their services. When they started that process they were surprised by a couple of things – one was the larger the customer was the less satisfied they were with Microsoft. So they then formed a group to manage those set of customers separately from the rest of Microsoft business.

Out of that work came some interesting insights. One thing they learned is that all those companies were mired in complexity. What are some of the core issues from those complexities, and what are some of the best practices that come out of those companies?

They went and looked at the Educause data on most important issues, and were struck by the parallels with the private sector. The issue of funding for IT is high in both areas, as are security and identity management, and strategic planning. The issue of ERP implementation has largely been dealt with already in most large enterprises. In private enterprise security is still important but has become part of the system.

He’s surprised by how low the issue of Governance, Organization, and Leadership turned up on the latest Educause survey – in private sector companies it ranks much higher as an issue – governance is the glue that makes this all work.

He puts the issues into a taxonomy of Governance, Architecture, and Procurement.

Governance includes strategic planning for IT, faculty development support and training, Governance organization and leadership for IT.

Architecture includes security and ID management, Admin and ERP systems, infrastructure management for IT, elearning, portalks, web services

Procurement includes funding, strategic planning, and support and training. How do you make sure the procurement cycles map to the rapid development of technology? This is a huge issue for governments.

In plain terms:
- in governance you deal with competing needs of many diverse stakeholders (how do you satisfy demand while keeping control of stability?), more demans than capacity, everyone is an IT expert

- Architecture – unless you have good architecture that is well managed and has a long-term plan it is very difficult to plan for an manage the complexity.

- Procurement – the budget process.

The GAP principles – derived from the best in class companies in how they manage IT.

Thesis
- Economic pressures of the early 200s lead leading companies to develop a set of best practices in IT governance, architecture and procurement: The GAP principles.

- Many higher ed institutions continue to implement GAP approaches which leading companies evolved away from in the late ’90s

- Higher edu adotpion of the GAP principles would enable accelerated deployment of new services and technology

What are the principles?

Governance:
1. IT is a service provider to the business. – Buiness units and information technology organizations need to be intimately linked through managed engagement processes.

2. The CIO requires real authority – CIOs need effective authority to mandate architecture standards across organizational boundaries. This is absolutely critical. The best of class companies have CIOs with the authority to set and enforce standards. This is a thin layer of authority which runs horizontally across the entire organization.

Architecture – Good architecture demands abstraction. Too much of what we build is tightly vertically coupled. Increasingly what we need to do is build flexibility built on open standards.

Procurement – Architecture is the foundation – a long term strategic model is required for core architecture procurement. Service orientation in architecture enables flexibility. SLAs are ok, but they tell the service provider the minimum they need to know, so they’re not the end-all.

Over the history of enterprise computing, nothing has gotten simpler over time. The late 90s we saw the IT “abyss”, with IT spending growing rapidly (no old stuff was being switched off), operations and maintenance dominating IT budgets (that’s still the case today – about 60% of budgets are spent on this, with only 28% being spent on adding new value), the complexity of distributed computing environment was exploding, and new development was ineffective. (1997 McKinsey research study).

Three catalyst events:

- Remediation of systems for Y2K – this was the first time organizations understood what IT systems they actually had, because they had to inventory.
- Stock market crash and bursting of the internet bubble
- september 11 attacks – told companies that the world is not predictable, which had a big affect on the trend towards outsourcing.

What do leading private sector organizations look like today?

Architecture:
- the web as the fundamental fabric – open stanadards, xml, http, etc. internal as well as external
- application abstraction through service orientation. So need to know what the core services are that need to be developed and then delivering them in abstract ways
- Systems abstraction through virtualization – fully virtualized data centers. This is very big in the financial services industry. Compute, disk, memory, IO are just a pool of resources in the data center, which can be allocated on demand.

Governance:
- Federal models. There is a CIO empowered to set standards for infrastructure that have to be implemented company wide. Includes desktops, middleware, and service infrastructure. CIO has the board’s authority to mandate that all development will use these standards. Having account managers, sitting day-to-day inside the client units is a best practice – making the standards understandable to the clients and feeding back the information from clients on business needs to the IT organization.
- Architectural “hegemony” – Shel points out that in research institutions you need to plan for those disruptive technologies that will arise and break the architecture.

Procurement:
- strategic partnership – picking vendors whose products are committed to the set of standards that are being implemented.
- The rise of shared service models – how do you make systems and services work together across units to service the customers. One example is in South Africa where they are trying to combine individual institutions into a system, and want to offer common services.

Benefits of good architecture – not about specific products, but about standards.
- Abstraction of complexity – making sure that applications all go through the same middleware layer, for example, to allow changes in the back end without application changes.

I asked about the conflict between abstraction and ERP implementations, and Jonathan replied that most well managed companies implement ERP in order to enforce standardization of business policies and practices in order to get a global view of their business, and use the ERP as a transaction engine, and then build a series of data warehouses that people interact with to get information. Not everybody gets access to the ERP, and nobody gets custom reports. At Microsoft the data warehouse applications provide HR data, for example that’s no more than 20 minutes old.

Technorati Tags: ecar2005, IT-architecture

Sandra Braman (University of Wisconsin-Mulwaukee)

Why does it matter?

- Research success is mission critical for many institutions, which means you need researchers. The Ability to do work is central to researcher identity. Serious researchers are willing to trade salary or switch institutions to improve support. It’s clear to researchers that IT are collaborators, not just service providers.

How do we know what we know? Direct and indirect info from national reports, conversations with faculty, anecdotal & systematic reports from CIOs, scholarly publications on research trends and methods, and trade press reports.

Factors affecting research use of IT – Disciplinary cultures; professional development on computational techniques (more widespread at elite institutions); institutional and general incentive systems – there are many ways in which research trends (like collaboration or development of new algorithms) are being undermined by incentive systems; Efficiency – how do we evaluate the efficiency of research? Trade-offs will be made in how people use technology based on efficiency – if I have to add metadata to get data into an archive, it won’t likely happen; Relationship between research & teaching – the use of research computing among grad and undergrad students is growing; Diversity of research approaches – people use high performance computing in conjunction with other research methods.

Institutional issues: competition for resources; history of privileging certain faculty and units; emphasis on homogeneity – can generate problems for researchers; assumptions about activity in units – IT may not be engaged with units new to research computing, but the assumption that support is happening in the unit may not be correct; inertial regarding institutional motivations.

Research culture issues: the rapid spread of computationally-intense research across disciplnes, e.g. music and dance or databases of videos in humanities; speed and continuous nature of innovations in research methods (needs for training); generational issues.

Decision making about IT for research: Hiring commitments by deans etc without discussion with IT units; Resource allocation – faculty may want to participate; collaborative infrastructure development (Princeton’s new supercomputer purchase from funds shared across units); policy implementation – if faculty are in on development of policy they are more likely to abide by it.

Collaborative Decision making – multiple options not mutually exclusive. They are quite rare at present. MIT has multiple working groups that orient differently around research problems. Deans and chairs don’t often really have any idea what’s going on in the research areas in their units.

Computing needs – capacity; stability (and help with transitions); architectural flexibility – people who know about OS and research app architectures are usuall not talking to each other.

Training – there’s a gap between how you were trained in grad school and current practices. Inadequate reliance on current students – lots of issues with use of students in terms of knowledge transfer, security, etc. speed of innovation. Range of diffusion techniques – working groups for getting peers in communication. Institutional and inter-institutional synergies. Linkage with methods courses.

More about software – needs range from simple scripting to custom software creation; software specialization as national institutional niche; finding researcher-authored software (NSF is talking about funding software archives)

Data needs: Collection; storage; preparation; presentation

Storage & preparation – multiplicity of types of storage (project-specific repositories to long-lived data collections of global importance) – UCSD is offering up 100 years of data storage to researchers from any institution. Multiplicity of storage venues. Rising & complex preparation needs. Policy issues (access, control, raw vs. cooked, – feds are pressing for release of raw data to federally funded research; etc).

IT & Ontologies – NSF is funding lots of work in metadata and ontologies. Driven by effort to bring info architects and disciplinary scientists into system design. One approach to user-centered design.

The new big two issues – more support for learning, adatpting, and writing software specific to their research problems; Researchers need help managing their data as it enters worlds of public presentation & long-lived data archives. UMich has a lib school training work for disciplinary specialists to do ontological and metadata work. Peter Murray from UMBC quarrels with these two issues – the hot topic is sophisticated pre and post-award information systems. Faculty and PIs want to reduce the administrative burdens. Everybody’s dealing with compliance.

I didn’t see any mention in this presentation of what is probably the biggest issue for us, which is demand for housing research computing in a centrally run data center environment. That need is being driven by security and recoverability issues.

Greg Jackson makes the great point that this analysis doesn’t recognize that many of the shortcomings are the results of tradeoffs made as a result of incomplete analyses of cost, risk, and opportunities. We need to do the analysis of which services are actually worth spending scarce money on.

Technorati Tags: ecar2005, research