IS YOUR CEO OUT OF TOUCH OR BEING MISLED? 02-14

IS YOUR CEO OUT OF TOUCH OR BEING MISLED?

A Troubling Result

One specific result I’d like to delve into is the fact that CEOs have a much rosier picture of how data-driven their organizations are than do those down the chain. A few of the key statistics are:

While 47 percent of CEOs believe that all employees have access to the data they need, only 27 percent of all respondents agree that they do.

Similarly, 43 percent of CEOs think relevant data are captured and made available in real time, compared to 29 percent of all respondents.

CEOs are also more likely to think that employees extract relevant insights from data – 38 percent of them hold this belief, as compared to 24 percent of all respondents and only 19 percent of senior vice presidents, vice presidents and directors.

This set of findings seems to have struck a nerve. During every media interview regarding the survey, I was asked about these figures (see these pieces at Forbes and CIO.com). My initial reaction was that some CEOs may be a bit out of touch. Upon further reflection, however, I have decided that this conclusion is unfair in many situations. In fact, it may not be the CEOs that are the problem at all. I believe that in many cases the CEO is being misled.

Is Your CEO Being Misled?

Let me clarify right away that I am not suggesting that there is some vast conspiracy to mislead CEOs. I believe the disconnect comes about from the way that information naturally works its way up the corporate hierarchy.

Imagine a director-level employee being provided a status report with a list of things that are going well and others going not so well across a range of initiatives. When passing the news up to the VP, the director is often going to naturally spin the good as positively as possible and downplay the bad. The director may even skip a bad point or two in the hopes that the situations can be remedied before anyone up the chain needs to worry.

Next, the VP employs some similar cleansing and scrubbing before providing an update to whichever officer he or she reports to. That officer then applies a bit more scrubbing before talking to the CEO. The end result is that the CEO comes away with a more positive picture than is warranted even though nobody intended to be misleading.

This phenomenon certainly isn’t unique to the processes around being a data-driven business. However, an organization can’t be truly data-driven until it is willing to look in an honest, unfiltered, unbiased way at whatever the facts are that data holds, both good and bad. In other words, in a data-driven organization, people should be comfortable providing the unvarnished truth to the CEO and the CEO should expect nothing less.

Being Data-Driven Is All About Objective Facts

There will certainly be instances where an individual’s pride or bonus will be harmed by the facts presented by the data and the analytics derived from that data. Part of being data-driven, however, is to prefer objective, factual assessments over subjective (often political) assessments. If my numbers are bad when reported factually and transparently, at least we all know how bad the numbers are and I know exactly how much I need to improve them. I’d prefer that to someone deciding my numbers are good or bad based on the mood they are in that day.

As your organization continues down the path of being data-driven, consider a survey of how wide the gap is between your CEO, senior management, and the broader employee base when it comes to the use of data and analytics in the organization. If there is a gap, make it a priority for everyone to focus on closing it. After all, the CEO must provide the support needed to fix problems and build on success as the organization progresses down the road to becoming data-driven. This isn’t possible if the CEO is being misled about the current state of the organization.

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Big Data and Data Center Operations 02-12

Big Data and Data Center Operations

Scott Koegler recently wrote a post titled ”Use Big Network Data to Predict and Avoid Network Problems” where he describes the use of data analysis and predictive analytics by IPSoft. Scott wrote:

"By turning predictive analytics inward to track where breaks happen most frequently, IT and network admins can set more accurate thresholds for recurring issues, positioning themselves ahead of any damage.”

Big data and predictive analytics are a great fit for the data center and IT operations, especially within the modern data center. There’s a great deal of data being generated and managed within IT operations, and the approaches and systems found within big data can help better understand and manage operations.

The example that Scott (and IPSoft) used is one that can provide value for any organization because it allows IT operations to understand (and predict) when breaks or issues might arise within the data center, network or remote office.

Imagine how impressive it would be for an IT specialist in a central office to get a notification that something in a far-flung branch office is amiss. Imagine again how that notification could tell IT staff exactly what was wrong and provide a recommendation to “fix” the problem before it actually became a problem.  This capability is available today with predictive analytics and data analysis.

Using predictive analytics and other big data approaches to identify bottlenecks, manage incidents and fix issues faster is the next logical step for data center and IT operations.

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What executives should know about open data 01-17

What   executives   should   know   about   open   data

Novel and more accessible forms of information from government and private sources represent a new and rapidly growing piece of the big-data puzzle.

Not all data that’s valuable is internal and proprietary. 

New initiatives by governments as diverse as those of the United States, Mexico, and Singapore are opening the spigots of readily usable public data. Corporate information too is becoming more “liquid,” moving across the economy as companies begin sharing data with their business partners and, sometimes, consumers. 

Also surging is the richness of the information from data aggregators, which are assembling, rendering anonymous, and selling (to interested third parties) a wide range of data flows. Then add huge volumes of data from social-media interactions, available from providers of digital platforms such as Twitter and Facebook

These new sources of open data represent an expanding trove of largely unexploited value. One everyday illustration of open data at work is a smartphone app that uses real-time data (provided by transit authorities) to tell commuters when the next bus or train will arrive. Using open or pooled data from many sources—all the businesses in a particular sector, for example—often combined with proprietary big data, can help companies develop insights they could not have uncovered with internal data alone.

Demographic data, financial transactions, health-care benchmarks, and real-time location data are among the myriad new information sources a company can exploit to create novel products and services and to make its operations more effective and efficient. 

New research from the McKinsey Global Institute, the McKinsey Center for Government, and McKinsey’s Business Technology Office suggests that $3 trillion or more in annual value could arise from the use of open data in applications across seven domains of the global economy (exhibit). About a third of those potential benefits would involve the use of benchmarks to identify areas for improvement.

Open data can help unlock $3 trillion to $5 trillion in economic value annually across seven sectors.

Whether or not individual executives at large companies choose to work with open data of various types, the magnitude of the value at stake suggests that some of them will—and that these applications will probably affect a wide range of industries, markets, and customers. 

Layering open-data mandates into the ongoing development of data and analytics strategies by considering both the use and sharing of more liquid data should therefore become an increasingly important priority for a wide range of companies. Here are a few examples of open data’s potential:

·         Energy exploration. As new technologies have made it possible to drill in a wider range of geological formations, reservoirs have become more complex. That’s raising costs and risks—estimated ratios of prospects to explored targets can be as high as 50 to 1. The sharing of information on drilling permits and on seismic and other data across companies could reduce the number of dry holes and help optimize investments. 

·         While the widespread sharing of seismic data is unlikely, sharing among even a few companies could produce significant new value in the oil and gas industry. 

·         Governments keen on maximizing resource wealth could take the lead in structuring processes for granting permits so that grants of initial drilling licenses would require greater sharing of seismic data. Sharing data on projected costs and development timetables (through third parties) could establish benchmarks that, we estimate, would reduce per-project costs by 15 to 25 percent.

·         Consumer insights. In the consumer-products sector, sharing data among retailers and manufacturers in limited circumstances—avoiding exchanges with direct competitors, for example—could lead to marketing approaches not possible with proprietary data alone. 

·         Take Nectar, a UK-based program for loyalty cards, which can be used at Sainsbury’s for groceries, BP stations for gasoline, and Hertz for car rentals. Sharing aggregated data allows the three companies to gain a broader, more complete perspective on consumer behavior, while safeguarding their competitive positions.

·         Agriculture. San Francisco–based Climate Corporation combined more than 30 years of weather data, 60 years of data on crop yields, and multiple terabytes of information on soil types—all data from public sources. 

·         With that reservoir of historical information and real-time data flows, the company offers fee-based advice to farmers and customized crop-and weather-insurance products based on sophisticated algorithms. The company was recently acquired for about $1 billion by Monsanto.

Other possibilities abound. Premium pricing for some goods could be facilitated if companies shared detailed information about products, such as the materials they use or the conditions under which they were manufactured (for example, with renewable energy).

 On the flip side, open-data applications may also create new areas of consumer value. In a budding trend known as MyData, organizations share information they have collected about individuals with them, in useful forms. Patients could access targeted medical data from a hospital, for instance, to help them manage their health.

Powerful as open data can be, many companies have valid concerns. Consider the sharing of data to establish industry benchmarks. Even if a company uses a third party and gets assurances of anonymity, there’s always a risk that its identity might be revealed and that competitors could see how well or poorly it was doing. Shared data also could give away sources of competitive advantage or compromise intellectual property. Similarly, tapping social data could heighten privacy worries among consumers.

Still, it’s hard to imagine that the open-data wave will slow down. 

Third-party open-data aggregators will certainly proceed to sell and publish corporate data, such as customer ratings, safety records, defect complaints and recalls, and comparative price data. Open-data initiatives also continue to proliferate in the public sector. In June 2013, G8 governments adopted an Open Data Charter, which establishes the expectation that the default policy should be the open publication of government data. 

Traditional competitors and entrepreneurial attackers can take advantage of open-data sources such as social-media comments and crowdsourced ideas to come up with new products and services. Open data, in short, seems to be another of the many relentless shifts in the digital landscape to appear unexpectedly, create new opportunities and strategic complexities, and leave established players with no place to hide.

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Converged systems usher in data center transformation 05-19

Converged systems usher in data center transformation

Remember the good old data center? It's on the way out thanks to the rise of converged systems. Gone are the twisted cable masses that connected many servers to one another and the SAN, while an overburdened cooling unit tried desperately to keep the temperature below 80 degrees Fahrenheit.

Converged infrastructure puts multiple servers, networking components -- and sometimes storage -- together in one box and includes a management platform to tie it all together. In these converged systems, hardware is managed as a service and delivered by an internal Platform as a Service (PaaS) cloud infrastructure. The goal here is to enable IT shops to be agile and rapidly deliver assets to the business's users.

A converged infrastructure system is one way to get a handle on hardware costs. Often, IT equipment consumes more than 70% of the IT budget. With a traditional approach, where IT is made available insilos, many resources are available and paid for, but sometimes aren't used at all -- the phenomenon of IT sprawl. Based on the current business demands on IT, this model isn't cost-effective anymore.

Customer demand for IT services in the office and on the road has increased dramatically. In those situations, it's not an option to order new hardware and wait days -- or weeks -- before it can be delivered. In a converged infrastructure system the hardware is already there, it just needs to be deployed or provisioned.

To some extent, a converged infrastructure system is not just a hardware platform, but an overall approach to IT. In such a system, resources like storage, servers, networking, power and cooling and security are all brought together in a pool, from which resources can be allocated when needed. An essential part of the solution is themanagement platform used to bring all these parts together and make them available on demand.

In a converged system, everything is virtualized. That means that server virtualization, storage virtualization, network virtualization and I/O virtualization are used together and made available from one integrated management interface to deliver resources on demand. This tight integration between virtualization and hardware makes it more difficult to see components as individual pieces instead of one integrated entity.

To a certain level, an IT shop can create a converged infrastructure system by standardizing and consolidating its technologies. What currently makes it difficult to rapidly deploy PaaS in a cloud environment is the lack of integration and standard components. Once blade servers replace rack servers, it is much easier to develop a management interface to allocate those servers on demand, together with the associated storage and networking. Currently, industry-wide standards are still lacking; that is where different vendors come in with varying technologies.

Current players in the converged infrastructure game

Right now, vendors like Hewlett Packard, IBM, Dell and Cisco are pulling their hardware together and offering it as a converged infrastructure system. At this early stage of development, most vendors are looking inward only; the focus is on integrating their own parts, not making them compatible with other vendor offerings. It's a new market and each vendor wants to be the market leader -- there's a lot of money to be earned.

As it stands, there are a few major players, but that number is increasing rapidly. Here's a short list of product descriptions for today's top offerings.

HP Converged Infrastructure

HP's Converged Infrastructure is not really a single product, but a system that brings different components together. It is comprised of four parts. The first is the HP Virtual Resource Pool, where server, storage, network and other key components are virtualized. Second, there is HP Data Center Smart Grid. This helps customers manage and optimize power in their data center by, for example, making it possible to switch off parts of the data center when not in use. Third is HP's Flex Fabric, which integrates the Ethernet and storage networks into one fabric for better management. Finally, HP has placed the HP Matrix Operating Environment on top of the hardware elements. This allows the allocation of resources from a single location.

Cisco UCS

Cisco's Unified Computing System (UCS) is as modular as the customer wants it to be and has several interchangeable options. The most important components in a Cisco UCS are the rack, fabric interconnects, proprietary switches and blade servers. All this hardware is managed from Cisco UCS Manager or UCS Express. UCS Manager is the main platform, tightly integrated with firmware on the different hardware components to make deployment of resources easy. UCS Express, on the other hand, is designed for remote management of IT infrastructure in branch offices; it integrates an original equipment manufacturer's version of VMware vSphere and connects to Cisco SRE 700 and 900 servers. These low-end servers have a maximum of 8 GB of RAM and two 500 GB hard drives, and are typically designed for use in branch offices.

Vblock

Vblock is a system from VCE, a company that doesn't build its own hardware but focuses on integrating hardware built by others. In the V block model, the customer purchases routers and blades from Cisco that are connected to EMC Storage and joined with VM ware Virtualization to create one integrated solution. VCE builds the solution at their premises and delivers it to the customer site, which means that one or more racks filled with hardware are placed in the customer data center. The advantage of this approach is the work can be finished at the customer site in a minimal amount of time, which means there is little interruption for the customer.

PureFlex

IBM is another interesting player in the converged systems game. IBM PureFlex offers systems that are relatively cheap compared with the competition, targeting both large enterprises and medium-sized companies. What is so interesting about the IBM offering is how similar PureFlex systems are to the tried-and-true mainframe. In other words, the company has started doing again what it was already doing decades ago but in different markets.

Smaller converged infrastructure vendors making a splash

There are many other vendors in the market of converged infrastructure systems such as Hitachi, Dell, Oracle and NetApp. Their products align with the basics outlined in the systems above, where integrated hardware is sold with management interface software that makes it possible to manage all parts of the system.

The skeptic's view of converged infrastructure

Converged infrastructure systems have drawn the attention of some companies, but they aren't cheap. Some of the least costly systemsstart around $100,000, with prices easily rising to more than $1,000,000 per rack. The main argument vendors are using to convince their customers is converged infrastructure systems can cut down costs of operating the IT environment. But how useful is it to save a million dollars on people if you have to spend the same amount of money on hardware every refresh cycle?

Apart from price, on the current market there seems to be a concern that old technologies are just rebranded to be sold in a box as converged infrastructure systems -- routers, fabrics, switches, blades and management software have all been around for a long time. Maybe a converged infrastructure system is just a rack filled with hardware that is organized in a better way and comes with a bettermanagement interface. And if that is the case, the customer might have other choices than to buy it all from one vendor.

Converged infrastructure systems are an important step forward in the configuration of the data center, especially since they allow the data center to provide PaaS services. Currently, we're just at the beginning of this game -- characterized by huge investments by the different vendors to develop a platform that works. As a result, interconnectivity is not on the list of developers' concerns, and as the systems are sold as an entity, it is difficult to integrate parts of other vendors. In the current market, there's a huge risk of vendor lock-in at high prices.

Developing converged systems for the future

The most important development that needs to happen for converged infrastructure systems is making them open. It is only a matter of time before customers start asking how to integrate products from other vendors, and someone comes along to make interoperability a unique selling point.

VCE's Vblock already makes small moves in the interoperability realm, but it is still tied down to a few specific vendors. Once the first vendor has started to really open its product, other vendors will follow and cheaper parts will enter the market -- with prices dipping to more reasonable levels as a result.

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How does the OpenFlow protocol ease traffic in the data center network? 05-19

How does the Open Flow protocol ease traffic in the data center network?

Stephen J. Bigelow

What is the OpenFlow protocol and how does it affect my data center's network?

As modern businesses deal with larger amounts of increasingly sophisticated data, the underlying efficiency of the data center network is becoming problematic. Switches and routers have traditionally used standardized protocols such as Open Shortest Path First, Routing Information Protocol and Intermediate System-to-Intermediate Systemto move traffic packets across the network, but as more workloads compete for limited bandwidth, the emphasis is shifting toward greater traffic efficiency. The emerging OpenFlow protocol aims to provide this efficiency.

A critical part of switch-and-router design is the ability to decide where a packet needs to go and quickly send it to the proper destination. This requires network equipment that can manage a control pathway and a data pathway on the same device, which most do. For example, a switch looks at a packet, decides where the packet needs to go andforwards the packet accordingly.

The OpenFlow protocol's communications approach allows both of these functions to be physically separated. The OpenFlow-compliant switch would still handle packet forwarding, but the switching/routing decisions are offloaded to a separate OpenFlow controller. The controller would then communicate with switches and other equipment using the OpenFlow protocol. The protocol defines detailed messages to perform tasks such as "send packet" or "modify forwarding table," and it defines status messages such as "packet received" or "get statistics."

When an OpenFlow switch receives a packet that it knows how to route, it will simply forward the packet accordingly. If the switch does not yet know how to handle a packet, it will forward the packet to the Open Flow controller to make a forwarding decision -- or even elect to drop the packet -- and send that decision back to the switch for future use. OpenFlow is an underlying technology needed to enable software-defined networking.

The goal of OpenFlow is to allow the development of creative and efficient routing and switching protocols for the data center network. It provides an enterprise with more versatility and networking options than might otherwise be available with traditional networking equipment using access control lists and conventional routing protocols. OpenFlow is sometimes used in situations that involve VM migration, mobility or network security along with already-established traffic types such as streaming media, storage or Voice over Internet Protocol.

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