For the past couple months, I have been working to understand Intel IT's innovation model ... specifically, how do we create business value with IT investment.  I have come across many approaches, opinions, projects, programs and more.

One of the key answers and best practices that I have found sits within a small team of Intel IT employees that is led by Martin Curley, Director of IT and co-founder of the Innovation Value Institute (IVI).

The IVI and Martin's role and goal in developing the IVI was written up in an article online at InnovationManagement.se, titled "intel Initiative Aims for More IT Enabled Innovation"

This article does a nice job summarizing one of the core IT governance tools we use internally inside Intel IT to drive innovation for the purpose of creating business value.  Originally formed through a strong link between NUI Maynooth and Intel, the consortium’s more than 30 members are among the world’s leading companies such as Chevron, Google, SAP, BP, Ernst & Young, and BCG.  While Intel IT has been using this model (the IT Capability Maturity Framework) ourselves for a few years we are not alone.  I'm told that over 200 companies utilize the resources and framework developed by the IVI in helping create more value through IT investment.

Learn more about the Innovation Value Institute

What tools does your IT organization use to create business value?

Chris

I was recently involved in a project where Intel IT SMEs from disciplines including Server, Storage, Data Center, Network, and Finance reviewed and updated our Data Center Strategy (Intel IT Data Center Solutions: Strategies to Improve Efficiency) for Intel IT.  The primary focus of the paper was to provide an update on value realized, shifts in strategy, and key execution lessons learned.

Our execution highlighted the need for finance to participate as an active partner in the influence planning and internal communications.  At some point, especially in economically challenging environments, cross organization investment decisions boil down to a tradeoff between limited resources and a number of good projects. Being able to clearly articulate the value added by a "portfolio of projects" (like the Data Center Strategy) and how you will track progress doesn’t mean that the project(s) will be funded – but it does increase the likelihood that you will be in the game at the end.  For us, having this coordinated communication strategy for technology solutions,cost efficiency, and operational efficiency was a key consideration for successful execution. 

We currently estimate that the cumulative projected financial impact over eight years will be ~$500-650M NPV - this range has changed in upper and lower limits based on updates to forecasts.  Over the first three years, Intel IT has realized ~31% of the projected benefits through execution to the Data Center strategy.  The primary value driver has been the impact of our server strategies (multi-core refresh and virtualization) that enable demand growth within the existing data center footprint and affordability targets.  Moving into 2010, we are evaluating new forecasting and value metrics to enhance customer reporting of data center activities.  This approach will incorporate our activity driver methodology into comprehensive unit costing and forecasting framework, creating a holistic cost forecasting process to improve future decision making.

One area currently under review is establishing the right unit of measure for a data center infrastructure housing different compute environments.  Is this something you or your business partners are exploring or looking to explore?

It is Time for a Data Security Revolution!

Information technology has lagged behind society’s skyrocketing need to manage and secure data.  Information is growing exponentially and our demands for control and oversight continue to develop rapidly.  Efforts to create or improve current paradigms are fractured and have failed to reach the tipping point of the maturity cycle necessary to catch up.  We have failed.  It is time we shed our entrenched archaic ways and leap forward to revolutionize how data is protected and managed.  The confluence of changes in our culture’s expectations of data, demand we succeed.  A revolution in data security is coming; we can either lead or be trampled by it.

The problem

The world is demanding more control, security, oversight, and awareness of where our data is and how it is being used.  This includes information generated and processed at work, as well as our own personal information including financial, health, and privacy data.  As a society, we are just starting down the road to explore data loss prevention issues, privacy expectations, digital rights management, and electronic discovery requirements.  Additionally, we are just beginning to understand the vast, hidden, and expanding world of data breaches, identity theft, user profiling, and online victimization.  Intellectual property controls are more important than ever to businesses in the information age and the social networking phenomenon is opening our eyes to the need for better security and management of individual’s data and the systems which control it. 

Yet the current behaviors, tools, and infrastructure is vastly insufficient for what we need today and the gap is increasing, leading to a critical failure point in every way for what will be needed a decade from now.  As fast as technology evolves, it simply cannot keep pace given the confines of current structures.  We will be left with a snarl of vague and unrealistic regulations, unsatisfied community demands, incompatible point solutions, tools which can’t scale, and an entire generation of information victims.  A radical change is needed!

The storm is brewing

A confluence of conditions is manifesting to create a perfect storm for radical change.  Consider the following social and technical changes which will change people’s opinion:

·        Data exposures are becoming public, showing the terrible depth of the problem

·        The number of data victims, for identity theft and online crimes, is increasing as are the losses

·        Data, system, and privacy regulations are emerging across the world with complex variations, creating severe challenges for global compliance, interpretation, and compatibility

·        Social media users are realizing the honeymoon is ending, their data is exposed, and being used in ways they never intended

·        Malware is reaching epic proportions.  The trend is shifting to target capturing victim’s data

·        Individual opportunists, organized criminals, and nation states are actively working to control systems, data, and networks

·        Surveillance, profiling, and filtering controls are becoming mainstream to target or seek control of user data

·        The sheer number of people and businesses on the internet is reaching a critical mass to determine how the world communicates, and the engine driving an exponential growth in the amount of data being generated

This problem may be complex in the details, but it is simple in principle.  Basically, we manage data poorly.  If I create a document today and email it to a co-worker, I essentially surrender almost all control.  In a week’s time, I will have virtually no idea who has seen it, how many copies exist, how long it will stay buried on storage devices, or what modifications have been made to it.  I have no control to update the copies, control access, or revoke the files.  Chances are good that after a year I will likely lose it myself or forget the content of the document.  It is terribly inefficient and represents poor overall management of data.

This situation presents as both a technical and behavioral problem.  The personal computer revolution has bestowed the tools to easily create and store data.  The pervasiveness of the internet established the unprecedented ability to share and disseminate information.  The natural limitations of the pencil and paper generation supported modest but adequate physical management solutions.  The creation, distribution, and control were tangible and restricted to local resources.  Our newfound ability to generate and distribute information has not been coupled with equitable management solutions.  Caught in the euphoria of new freedoms, we ignored the capabilities to control and secure.  The shortcomings of technology have been tolerated due to an apathetic and disjointed demand from society.  We have failed as consumers to recognize the importance of our data and the deficiencies in the realization of how it should easily be managed.

It’s the 21st century; do you know where your data is?

Today, data is easily created, lost, transferred, edited, stolen, abused and destroyed with very few mechanisms to prevent, detect, or respond. 

Consider the following:

·        We don’t track who creates files and who owns them

·        Rarely do we consider if files should be secured or how

·        We don’t take steps to determine who should access, view, or edit files and where they can be stored

·        Destroying data after it is no longer useful, is a foreign concept, as is who should be responsible and when

·        We don’t understand who, at any given time, has possession of our data and how to effectively recall it

·        We have little insight to data content.  We rely on short and sometimes cryptic filenames to give clues, but we don’t comprehend contents in a meaningful way

·        Sharing data is mostly ad-hoc for specific files or locations, with little thought of content or other security factors which should be considered

In summary, we are poor custodians of data.  In fact, people keep better track of the clothes in their closet than the information assets they create every day.  I would wager you know where your clothes are, which are clean and which are soiled, and you have designated places for both.  You regularly maintain your wardrobe by cleaning, pressing, matching, folding and storing clothes in an organized manner.  Items are added, minor repairs made, and eventually clothes are purged when they no longer fit, are outdated, or simply not needed.  You plan and may budget when new clothes are required.  Depending on your age and habits, you may even have your name on them for ownership identification.  You organize your closet for easy searching and you know which articles have been loaned out and to whom.  For important items you would likely detect if they went missing and probably have a good idea of likely suspects, as you know and control who has access.  So why do we do such a good job at managing our clothes, yet such a miserable job at managing our data?

People have not yet put the mental pieces together, but they will.  When they do, they will demand technology deliver a solution.  Revolt will be at hand.

Current efforts

A number of current initiatives have been struggling to gain modest traction but will always lack the ability to deliver a complete solution.  Digital Rights Management(DRM) is well known in the online music circles, focusing on file based locks.  Data Loss Prevention(DLP) is a collection of practices and tools which can scan, classify, and block inappropriate transmission of data. 

Structures like Role Based Access Controls(RBAC), Mandatory Access Controls(MAC), Discretionary Access Controls(DAC), and Lattice Based Access Controls(LBAC) have attempted for years to establish controls within homogeneous and small environments, but rarely work as intended in large mixed environments like modern networks.  A variety of secure data repositories have emerged, which do a stellar job protecting a few critical items akin to a vault, but are largely inaccessible, inconvenient, and not scalable.

A quick summary of current solutions highlights why they are not scalable, will fail to provide a complete solution, and likely never be widely adopted.  Each of these does have its place and function but overall they will not deliver what is needed; a comprehensive capability to manage data security. 

1.      Vault solutions:  Secure some files in a locked system or repository and provide access via custom interface applications.  Not scalable for vast amounts of data, poor accessibility, high level of permissions management needed, inconvenient to use, and the trend to use proprietary software will keep the price tag high

2.      Scan and classify DLP systems:  Can apply controls both on clients and networks but relies on rules which are complex and a nightmare to maintain.  Ultimately this is why they eventually just get ignored.  Sustaining accuracy is not practical in environments which change and grow rapidly

3.      Scan and alert/intervene DLP systems:  Similar to Scan and Classify DLP systems, with an added benefit of intervention. Blocking suspect traffic and communications is a double edged sword, which requires high overhead to insure it does not interfere with legitimate business.  These suffer from the same drawbacks as their cousins.

4.      Employee policies:  Policies which rely on manual intervention are hit or miss.  For simple straightforward decisions they can be quite effective.  For complex data decisions, changing environments, and potentially vague situations they fail miserably.  People simply don’t act consistently when faced with complex decisions

5.      System policy (MAC, DAC, and LBAC) solutions:  System based solutions which can work well while data stays on the system but fails when collaboration across systems and users is required.  They simply lack the applicability, scalability, and compatibility across a network with various uses and complex situations of collaboration and security.

6.      Group/role access policies (RBAC): The natural evolution of the MAC, DAC, and LBAC concepts, can work great for small groups and data in an environment which does not change often.  As the numbers and data size grows, the administration increases and ultimately does not scale efficiently.

7.      File lockdown systems (DRM): Locking down files with digital rights (DRM) can work in situations needing a simple access control.  Allowing a file to be opened or not, for example.  But it does not work well when a multitude of access options are needed and other controls are required.  Compatibility also poses a problem when sharing such files across systems.

8.      Secure critical files and data solutions:  File encryption is the major player in this field.  Target only the most critical data and files, and focus on protecting those.  Not scalable with the increasing amount of data organizations are processing and the shift of data across a much broader user and system landscape.  Works great for handfuls of people with a small number of files needing protection.  Those days are gone.

9.      System data protection solutions:  As file encryption has too much overhead necessary to scale, just encrypt the entire system and network.  Works great for lost laptops but does little when the user has logged in and everything is now easily accessible.  Network encryption only protects against sniffing.  A good evolution but not nirvana.  It is a one trick horse for confidentiality.   

10.  Do little to nothing and hope for the best.  Don’t laugh.  You might be surprised with how many financial, health, educational, and governmental systems followed this model for most of the past decade. 

The list goes on.  This is not comprehensive, but does give a taste of some stovepipe solutions which are struggling to evolve even slightly and will never leap forward on their own to meet what will be demanded.

Overview of solution

How do we succeed?  We combine some of these technologies, integrate into the base computing infrastructure, and ease in the necessary user behaviors into the fabric of how people create, use, share, and destroy data.  It must combine an object oriented definition structure and network based management controls. 

Four core aspects for identification, security, and management of files

Data objects must carry specific characteristics to enable the computing environment to effectively and efficiently manage security.  Although discrete parameters may differ based upon data type and parent organization, these aspects represent the necessary structures which work together to enable automation and to define security practices.  Additionally the characteristics themselves must be secured and compartmentalized.

1.    Confidentiality Designation – Level of sensitivity and confidentiality for the data.  This has implications on required controls for data at rest, in use, and in transit.  Also can define requirements for where and who can access and store the data.  Examples might be Top Secret, Secret, Business Confidential , Personal, and Public.  Classifications have implications to the Access and Handling aspects.

2.    Access Rights and Permissions – Who has ability to access, edit, store, copy, transfer, etc. the data objects.  DRM and RBAC technologies and DLP principles are a good start.  The object must securely contain the concepts of ownership and those trusted to use the data in different ways, including to open, edit, destroy, move, copy , and transmit.

3.    Content Synopsis, Tags, and Keywords – Identifying content supports indexing and understanding relationships between files.  It facilitates scanning and auditing against policy as well as automation for determining access, classification, and secure handling requirements.

4.    Secure Handling – Secure handling parameters determine retention, backup, destruction, storage, usage and transport requirements.  These can be set by a default policy and updated based upon other aspects.  Data Lifecycle Management (DLM) provide a good foundation for some practices.

These four aspects cooperate and influence each other.  If for example, file content changes to include secret information, the classification may automatically bump to a secret designation, the secure handling settings will force persistent encryption, and change the access rights to allow access by a smaller community. 

Cookbook of requirements:

This is the wakeup call for firmware, operating system, application and security solution providers.  To change how people manage data, from creation to deletion, will require the major players to work together with standards and Application Programming Interfaces (API’s).  We are not just altering one piece or bolting on additional security, we must change the fundamentals of the very infrastructure we use to manipulate data.

Some inroads have begun.  DLP and DRM systems have established expertise in some preventative, detective and responsive functions.  Social media is leading the way in many respects with tagging, sharing, collaboration and most importantly tracking and metrics.  On the most modern sites, an author can post a video and track how often it is watched, by whom, and if they are using it in other mash-ups.  A great deal of data can be gathered and if analyzed correctly, transformed into usable intelligence.  Social media is the looking glass for what is to come.

These requirements are critical for success:

·        Must apply system wide, embedded seamlessly in hardware, Operating Systems, and applications.  It must include all data which is created, viewed, modified, transported, or deleted by users

·        Must span across users, client systems, and into the backend infrastructure

·        It must be holistic in nature and apply  from creation to deletion (birth to death) for data and files

·        Must possess default security for creation, storage, transit, and when in use

·        Support at a minimum, basis functions of DLP, DRM, meta-data, content tagging, RBAC, client agents, data tracking, and control repositories

·        Maintain a centralized structure for metrics, audits, maintenance, discovery, and reporting

·        Distributed and centralized hybrid system supporting comprehensive scanning, indexing and auditing

·        Enable data tracking, verification, auditing, and ownership administration

·        End-user involvement and empowerment, to directly access and manage control systems and distributed data

·        System interoperability across separately controlled domains and networks

·        Establish end-user ease of use, manageability, and scalability at all integration points:

o  Straightforward setup with additional modular extensibilities

o  Default settings based upon role for confidentiality and handling

o  User interface validation of parameters, and extra owner options, when saving, editing, moving or transmitting files

o  Default access rights based upon groups, tags/keywords, and storage location (for example, inherited rights based upon storage location or of like files)

o  Escalation and resolution options when actions are prohibited by the system

Vision of Success

We have the intellect to succeed.  We can create a new paradigm which meets the needs of legal, privacy, security and most importantly the maturing expectations of everyday people.

Keys to strategic success:

·        Make the capability embedded, easy to use, and secure by default.  Minimize impact and overhead to the users

·        Champion behavioral changes of users and administrators, show the value

·        Drive client Operating Systems and Applications to conform and support standards

·        Leverage security tools to extend services and controls

·        Establish back-end infrastructure support via standards

·        Foster competition to drive affordability, scalability, support and continuous improvement

Key capabilities for value and functionality

·        Automated intelligent determination of initial core file aspects, with validation by users during file management requests (save, transmit, copy, etc.)

·        Automated security controls applied and enforced based upon file aspects and derived control requirements

·        Automated data cleanup, archival, and destruction based upon file aspects and settings

·        Data owners can easily search and organize their files both local and across the network

·        Data owners can easily take control to manage access, confidentiality settings, change file handling parameters, and revoke files across the network

·        Administration can conduct broad electronic discovery searches for files and data content, generate operational metrics, and gain an understanding of where sensitive data is located and how it is being used

·        Automated security alerting and logging to assist with detection of unacceptable actions, resolution to events, and predictive information to facilitate the establishment of future preventative controls

Example Use cases

New document creation

Capturing the meta-attributes at the point of creation is a critical step.  As a mock-up, this email was created and a default set of icons appear in the toolbar, showing the status of the 4 aspects.  These default settings align to Confidentiality Designation, Access Permissions, Content Synopsis, and Secure Handling settings configurable by the organization or user.  They establish base parameters but change dynamically as content is added.

As text is added, the system determines the content to match criteria which changes the classification, associates to a current project, adds to the content tags, and modifies access permissions automatically.  The icons change in appearance to show how the data will be treated.  The user can intercede manually by clicking the icons, which will open the user interface showing more options and configurations.

Saving, moving, deleting or transmitting data

A modified window appears whenever users attempt to save, move, delete or transmit data.  This confirms settings and if needed, solicits additional necessary data to complete the transaction.

End state vision

·        From creation to destruction, data is automatically classified, secured, and under the control of the owner

·        Additional capabilities extend to allow complex management, sharing, security, and tracking

·        End users are empowered to easily organize and revoke their data, control access, and know where it resides

·        Through leveraging technology, data files are treated like assets and security is efficiently managed across user domains

Conclusion:

Change is coming.  The underlying community, regulatory, and behavioral factors are present and becoming more prevalent.  The information technology and security industries must escape the façade and false hope of small improvements and truly revolutionize how data is secured and managed.  This can only be accomplished with aligned industry partnership, a realization of necessity, commitment to user efficiency, common technical standards, and most importantly a shared strategy.  It is possible.  Now is the time to think, discuss, and plan.

Watch Diane Bryant, Intel CIO, talks about the cash machines in data centers in this press breifing. Haven't heard about the amazing cash machines for your data centers yet?! Better check it out now: Installing Cash Machines in your Data Center

At a recent event our CIO, Diane Bryant, talked about our continued plan to replace old servers in our Data Centers (http://www.tgdaily.com/content/view/44213/135/). Here is a summary of her key points:

• Not replaceing servers could have costed Intel $19 million due to high maintenance and cooling cost
• Our plan of refreshing old servers with Nehalem servers will save Intel $250 million over 8 years

If you are an IT manager looking at where you can find extra dollar in your IT budget to invest in new technology, new innovation and new competitive capability for your organization, this must be good news for you! Moreover, if you do nothing, you are opening a hole in your IT budget.

Here is a recent white paper and a video we published to discuss our server refresh strategy and how we are getting the cost benefit Diane Bryant shared:

Realizing Data Center Savings with an Accelerated Server Refresh Strategy

We have also developed a Server Refresh ROI estimator so you can calculater the amount of savings you can get from these cash machines:

http://www.intel.com/go/xeonestimator

If you ain't satisfied, here is a video showing you how to use the estimator!

Go and install those cash machines into your data centers now! 8-)

I just read this paper authored by some of Intel's IT experts in the area of client management.  As an employee of Intel, I am now a huge fan of these rock stars.  Why? because they were able, through proactive IT management practices, reduce blue screens inside Intel's employee base by over 50% in the last year (Q2'08 to Q3'09).  There are now 3,000 fewer laptop blue screens than there were a year ago --> that is a huge productivity advantage for Intel workers.

Issue Tracking, Pareto Analysis and use of new management capabilities and technologies like Intel vPro Technology were at the center of these capabilities.

Read about how Refael Mizrahi, Shachaf Levi and Jeff Kilford made my life as an intel employee a whole lot easier by Improving Client Stability with Proactive Problem Management.  You Rock!

Chris

Someone send me this Dilbert* strip yesterday. Data Center is in such high demand even Dilbert is building one. He was having trouble getting power to run the DC with air conditioning. He thought the servers would melt to a toxic bomb. I think he might be happy to know that he could actually run servers without air conditioning in a data center and he wouldn’t need to turn the DC into a museum.

Last year Don Atwood, a regional DC manager in Intel, has done a proof of concept (PoC) to challenge industry assumption in DC cooling by running a high density DC with only a air economizer and no air conditioner. In the PoC, Don ran two DC modules in parallel – one with traditional air conditioner as control; one with air economizer as the POC test. After 10 months, other than dusty servers in the POC module, there was virtually not side effect found on the 900 servers in the air economizer module. The hardware failure rate in both modules was similar, contrary to many would have believed. The biggest finding from the experiment was that we were able to reduce 67% energy consumption for DC cooling comparing with traditional data center cooling approach. Not only the reduction in energy consumption contributed to the IT sustainability programs, we also estimated using this new approach in a large 10-MW data center would save US$2.87 million annually (based on cost of $0.08 per KWH).

Have you try running your DC without air conditioning? Do you have any other innovative way in saving energy consumptions and cost in your data centers?

* Names and brands are properties of their respective owners