Taken from a 2009 White Paper, this image shows the new competencies required from partners to make the transition from traditional reseller to Cloud Aggregator or Cloud Reseller. What Techaisle described was the opportunity to become either an aggregator, by becoming the equivalent of a “first tier” distributor (positioned between the vendor and resellers who then sell to end-users), or as a Cloud Reseller, selling directly to end users.
Competencies required for the aggregator include the ability to aggregate services and integrate them across services, either data across applications or building solutions between infrastructure, communications and application services. In addition, core competencies were/are needed in the areas of service provisioning and datacenter management. Then an Aggregator needs to be able manage reseller relationships with structured sales and marketing programs, implementation and post-implementation support for the channel, and tier 2 customer support for end users. Given these demanding requirements and the price pressure, it is not surprising that larger organizations like Dell have been the companies to aggressively pursue this strategy and taking advantage of an existing hardware and storage business to offer a full solution stack to resellers and Enterprise customers. As we have written on several occasions, the SMB channel is being squeezed by several trends including the rise of the Digital Channel, Self-Service Applications, Remote Management Dashboards, Plug-and-Play Horizontal Applications, and others. These make the aggregator approach difficult and susceptible to commoditization, more so given the additional challenges of recruiting, managing and supporting an additional tier of resellers. As a result, there has been a lot of confusion around how to make money as an aggregator, and the assumption that a solution has to include all layers in the stack: Computing, System Software, Storage, Network and Application. Even considering wholesale remote infrastructure availability, channels are confused about which layer to start with, how to choose the vendors, where to recruit staff, how much investment, how to migrate existing customers and many other questions have prevented many channel partners from making the move.
The other option for SMB channels is to move existing and new customers to cloud-based services, which still requires embracing new technologies, and figuring out how to add value through specialization, integration, customization and/or all-in-one provisioning, maintenance and support. With that as background, we can move into the topic in the headline: What the SMB channel needs from Cloud-based Service vendors. The partners here represent VARs/SIs, ISVs and SPs, and are more typical of the Reseller category rather than the Aggregator.
In a recent survey of SMB Channel Partners who offer Cloud-based Services, the most important need from Cloud Vendors was for an SLA that guarantees availability. SLAs were cited as most important by Service Providers and VARs/Sis with 61% and 59% respectively, which brought overall average to the top of the list at 53% of all partners surveyed. This is consistent with what we have heard directly from SMBs, who are using the SLAs as a proxy for the brand of underlying infrastructure and system software of the applications. The effect of this is strongest on hardware vendors, whose equipment is becoming increasingly commoditized by plug-and-play infrastructure and exacerbated by a digital channel that uses self-service interfaces and management dashboards instead of on site visits. In a similar vein, the next requirement also comes directly from SMB customers, who want access to 24x7 support services. As SMBs move to SaaS and Remote Services, outsourcing infrastructure and applications exposes them to more risk and loss of control, increasing the need for the security of a 24 hour Support Desk to reduce the perceived risk of “offsite everything”. These first two needs line up with SMB purchasing criteria, ironically two of the other most important factors are Price and Data Security. That they are not passed on as needs to the vendors probably suggests that these are largely under control – users also typically rated high levels of satisfaction in these areas.
Most of the remaining issues relate to two categories: Product Related and Partner Program Related.
Product Needs included better methods of integration, a broader catalog of applications and single sign on across applications.
Partner Program Issues included better notification of upgrades, changes and downtime – providing onsite training, having a policy concerning data migration to competitive products, and ability to offer discounts for paying annual fees upfront.
Vendors and Cloud-Services Aggregators should keep these needs in mind to develop the best Cloud Partner Programs, and SMB Resellers should use these vendor capabilities to select the right Vendor/Aggregator to work with as they migrate customers from a traditional offers to Cloud-based solutions.
Techaisle Blog
Looking at the Mashable.com infographic on China’s Internet speed and other stats, we started noticing similarities between where China is now and Korea was 10 years ago. Growth of broadband Internet availability is already remarkable in China, but we only need to look across the Yellow Sea - a one-hour flight - to Korea to see the real potential.
According to an Organization for Economic Cooperation and Development (OECD) report published in July 2012, South Korea's high-speed Internet penetration rate topped 100 percent for the first time among the group's 34 nations, making it #1 in the world for broadband usage. Exceeding 100% is possible based on the connected devices per capita rather than each individual in the country having broadband access. For comparison purposes, the US is at 76%
After a 10 year break, I visited Korea in 2010 for a month-long project with one of the National Universities. In the decade between 2000 and 2010, the level of infrastructure build out and ubiquity of free broadband wireless access, even in the smaller cities, was incredible.
It shouldn’t have come as such a big surprise; Korea has been making deep investments in national communications for over thirty years, beginning with a strategic move in the mid-1980s that separated voice and data traffic, effectively taking data away from the government voice monopoly, Korea Telecom, and giving a data monopoly to a company called DACOM, with the charter to develop a national plan for data networks. The economy was regulated at the time and the political system still very authoritarian. National policies (successive five-year plans initiated by strongman Park Chung Hee) dominated decisions about investments, especially in areas of finance, technology and industrial infrastructure.
One of the strategic initiatives was the national development of Value-Added Networks (VANs) that the conglomerate companies – Samsung, Hyundai, Lucky-Goldstar (LG), etc. - could use to connect their manufacturing operations with suppliers using ISDN technology. This telecom foundation was critical to the contribution of these companies in building an economy that grew from $2.7B in 1962 to $230B in 1989. GDP passed $1.5T (PPP) in 2011.
This brings us back to the point. There are a lot of similarities between China and Korea that could help us understand the potential explosion of Internet adoption and application in the PRC. Among the most relevant are:
Rapid economic growth: Korea’s economy grew at a compounded rate of over 8% between 1962 and 1989, laying the groundwork for it to be the 12th largest in the world today, despite a population of less than 50M. As seen in the Economist chart here, China’s GDP growth has grown at a rate above 10% since the early 1990s, and although it slowed significantly with the US downturn in 2008, it is still forecast to grow at an 8-9% rate through the end of next year, according to the IMF and major trading houses.
Infrastructure investment: Korea’s economy was managed through successive five-year plans that directed Bank of Korea investments deep into all areas of infrastructure and heavy industries, and these continue today, in a much more democratic - yet still pragmatic way, with huge projects to position the country as a commercial hub that can grow on the back of China’s emerging leadership role. In order to re-energize China’s economy the government poured over $630B into infrastructure projects in 2008/9. The second round, which seemed a little more cautious represented another $157B this year involving an additional 60 major projects. Even with this level of investment, there is a substantial IT gap that needs to be filled for SMBs to be able to automate effectively. Of the 3.7M SMBs in China, only 56% currently use PCs, while virtually all of Korea’s 3.2M SMBs have at least one PC and an internet connection.
Managed Economy: A large part of Korea’s success came from the ability to resist pressure to open up the economy and maintain a trade balance that spurred growth of a middle class, driven by domestic rivalry in the areas of steel, cars, consumer electronics, construction equipment, etc., followed by an explosion of exports in these areas. Korea’s strategic and geographic and political boundaries during the Cold War allowed them to resist this trade pressure. Situated between Japan, China and the Soviet Union, Korea’s security role superseded global corporate interests in agriculture, manufacturing and heavy industries allowing managed capital flow, political selection of winners, focus, hard work and sacrifice to build a robust economy from the ashes of the Korean Conflict. Also important was that the GDP per Capita only reached $5K in 1989, making it a little difficult to argue for changes that might have a destabilizing effect on the impressive string of results.
Now China has emerged as the new regional miracle and holds strong political, economic and military cards that will allow it to resist similar pressures and continue to exert control over its’ economy. While it remains very vulnerable to external forces such as financial volatility in Europe and the US, it has managed to control the areas of technology adoption and control of the mass (and individual) communications For example Google’s only true global competition outside the US is Baidu; the leader in the PRC so far, and let’s not forget that Lenovo, the PC brand that IBM sold less than 10 years ago to its’ major Chinese ThinkPad OEM, is poised to overtake HP and Dell this year as the global leader in overall PC shipments, not just notebooks. Another relevant example is that Samsung was a strategic HP OEM for high-end workstations and low-end servers in the 1980s using PA-RISC architecture. Intel won the war of the processors, making PA-RISC obsolete and Samsung became a global leader in memory chips and disk drives, which is now giving way to solid state memory, a fundamental component in the new generation of tablets PCs and other end-user devices. Oh yeah - Samsung is also a global leader in smartphones, shipping twice as many as Apple did last quarter; 50M vs. 26M. Oh yeah - they also supply Apple with a lot of important components. I would be scared too. But more to the point, Apple manufactures in China, just as IBM did with their flagship Notebook. Ironically, in the last few years Samsung emerged #1 in television shipments and has only been in that game since the late 1980s. This is not an argument for a managed economy - just some observations about long tail trends. My personal opinion is that Korea benefited from resisting pressure to open their economy too soon. I’ll let readers draw their own conclusions here.
Concentrated Population and Vertical Architecture: Korea’s Internet leadership benefited at least as much from the urban architecture as the government policies; maybe more. A small country with a rapidly-growing population and standard of living, Korea was transformed from a country of 1, 2 or 3 story cement block houses to a “Republic of Apartments” since the mid-1980s. In preparation for the 1988 Seoul Olympic Games, thousands of post-Korean War tenements and lower quality housing was razed and hundreds of 20-30 story modern apartment blocks took their place. The current apartment complexes have everything needed for comfortable living, including underground shopping centers and subway stops – almost like small cities. And typically they are modern and very well built - think New York - not $700 a month on the other side of the tracks. By concentrating 20M people into Seoul, the vast majority of whom live in these towering apartment blocks, the challenge of providing the last half-mile can be solved by bringing fiber to the curb and connecting hundreds of families at a time. Now consider that according McKinsey, China will have 221 cities with over a million inhabitants by 2025, adding more urban population than the total US population.
To accommodate this growth, the country needs floor building space equivalent to the land mass of Switzerland, or up to 50K 30-floor+ skyscrapers. If that is not enough to make the point, one of the megacities planned is supposed to combine 9 existing cities in the Pearl River delta into a single megalopolis of 40 million inhabitants, ringing Hong Kong with China’s largest manufacturing center. This optimism has been slightly dampened by the bursting of the property bubble that came with the anticipated growth of the area, lots of empty office space and apartments. Despite the local setbacks, analysts at Goldman Sachs expect a “soft landing”. Personally, I don’t think anyone can accurately predict where any economy will be in two years, but we use the tools we have.
There are other similarities such as national pride, a hungry population that is willing to sacrifice, work ethic and cultural bonds, but for the sake of brevity we don’t need to go into a lot of detail here.
The Elephant in the Room: Most people would agree the biggest single risk to China following Korea’s lead on Internet adoption is whether the government can hold the population down while they become increasingly affluent and aware of the personal freedoms and opportunities in other advanced economies. In Korea, the catalyst for the explosive growth between 1990 and 2007, when per capita GDP reached $20K from $5K, was the first peaceful transfer of power to a civilian government. All of the Internet adoption and high tech growth followed this major political reform, and would have been very unlikely without it. As described in our post about Managed Services adoption in the PRC Mid-Market, there is very quick adoption of the best new technologies (as long as they do not pose too much risk to the powers that be). China could take a much faster path to prosperity by relaxing the political control on personal freedoms - but speed is not the priority and the problem with making political predictions is that it is much too complicated to get right. But it only takes one person, a Gandhi, Gorbachev, Aquino, or in China's case Deng Xiaoping to make history jump instead of crawl. It is good to keep in mind that stranger things have happened; none of the experts predicted the fall of the Soviet Union in 1992 and nobody could have imagined Korea bailing out Russia – the patron of their arch rivals in North Korea.
As might be more evident in this post, I am a Korea watcher, not a China watcher. For an expert view on what is happening in China related to Internet adoption and social issues, this TED presentation by Michael Anti (aka Jing Zhao) is a good place to start.
Current penetration of Marketing Automation in the Mid-Market is higher than Small Business across the board and determines overall ranking within SMB segments. The “Currently Use” below represents either standalone applications or functions that have been enabled within Marketing Automation Suites. Our research shows that the number of applications, or enabled functions, has steadily increased from 2 in 2010, to 5 in 2011 and survey results suggest that will move to between 7 and 8 as an overall average for SMBs across all size segments. Once a quick win is apparent there is a lot of enthusiasm to move forward with new efforts.
We have also uncovered some interesting trends that will be the subject of upcoming posts and our SMB Marketing Automation report and Updates. These trends include a fairly consistent relationship between the adoption of applications, an order of operations if you will, between several categories of cloud based services and applications; once SMBs are unfettered from the linear HW, SW, NW, Integration cycle, they are able to adopt technologies in a much more strategic way. For example, adopters of SaaS CRM start immediately investigating Business Intelligence options as soon as they are up-and-running with their CRM Dashboards and Reporting – this previously unavailable functionality spurs investment in an effort to get more visibility into other parts of the business. Also, opportunity in Integration Services abounds as SMBs commit to Cloud-based architecture.
Current Use Key Points:
Only Email Marketing, Segmentation and De-Duping are more widely used by Small Businesses in the Survey, Mid-Market companies are far more likely to use the rest of the features.
For those who use Marketing Automation, Email Marketing, Campaign Management, Message Personalization, SEO and CRM Integration are the most adopted Marketing Automation Functions – driven largely by more aggressive usage within mid-market companies.
While the market is maturing and relatively new, basic requirements like the Top 10 listed above are laying the foundation for all SMBs, but soon after there is a divergence as requirements of small businesses, typically building out their block-and-tackle marketing productivity by enabling individuals, evolve into a need to build effective teams by tightening up process and collaborative capabilities in Mid-Market companies.
Needs Evolve with Size of Company and Level of Maturity
While Web-based Lead Capture and Campaign ROI Reporting were common objectives between the Small Businesses and Mid-Market Firms, other in the Top Five were different; SBs looking for more Web-based functionality like Social Media Monitoring, SEO and Analytics Dashboard, while the MBs were looking for more data-oriented functionality such as De-duping, Segmentation and Lead Scoring.
Level of integration value added opportunity for these scenarios is also different, and obviously grows as companies look to improve collaboration.
Wall Street Journal Article
This is an interesting article from the WSJ concerning how we are slowly allowing decision-making processes to move away from people and be handled by algorithms instead. It caught our attention at a time when we are completing survey work for Business Intelligence report. As discussed in an earlier post, one of the key trends in BI is how deeply it is being embedded into all kinds of applications , and this article is a good example. Please let us know what you think: comment, like, tweet or forward.
Laying the Foundation
Analytic software has evolved through several generations over the last 70 years from around WWII, when a series of unprecedented number-crunching challenges gave rise to Decision Support Systems (DSS) designed to solve problems such as best equipment production mix given material constraints, how to logistically support the Allied invasion of Europe, split the atom, or break the Japanese code. These kinds of problems tended to be monolithic, using stochastic models to find the best answer – and were a major catalyst to development of the mainframe computer.
Business Intelligence (BI) followed this linear and iterative approach with one that supported solving business problems, mostly operational, within divisions and departments of large commercial organizations, using more distributed equipment within a wider audience, i.e., Finance, Operations and Distribution. In the late 1990s there was an explosion of data resulting from widespread adoption of CRM, the killer app of the Client/Server era, adding mountains of Sales and Marketing Data to the volumes of operational information. There was a growing need to get a top down view of how performance in one area of the organization was impacting the others, to begin taking a more structured approach at understanding cause and effect, setting objectives and consistently measuring performance to improve results. BI was evolving into Enterprise Performance Management (EPM) - which is where market leaders are today.
EPM is characterized by using Business Intelligence software to understand the best performance scenarios, measure actual performance indicators (KPIs) and determine how to close the gaps, using exception reporting for most front office functions (CRM/SFA) and rules-based processing for the back office (Process Manufacturing/Real Time Bidding, SCM/Advanced Web Analytics).
Optimization Nation
Equally important as the individual BI technology advances are some of the underlying rules that have accompanied the evolution: Moore’s Law, Metcalfe’s Law, the Law of Accelerating Returns all drove exponential growth in production, adoption and utility. Over a 20 year period, these have resulted in a slow-motion Black Swan event based on the cumulative effect of technology investments, and having huge impacts on our society, including but not limited to the following optimization activities:
Economy – development of consumer mortgage products designed to optimize sales volume regardless of risk, bundling them into bonds to optimize profit on the debt, creation of derivatives to optimize transactions and create demand for increasingly suspect debt, development of new financial instruments that have no underlying value such as synthetic derivatives that truly have nothing but conceptual paper profits behind them, etc. By 2008 these financial instruments had optimized leverage to create risk greater than the combined GDP of industrialized world.
Employment – The WSJ article goes into depth about how algorithms have already replaced a hiring manager's decisions based on probabilities of how the employee might behave under certain circumstances. Employer choices have also been optimized by a flattening of the market caused by oceans of virtually unlimited supply from sites like Monster.com, 100K Jobs, Dice, etc. Middle management has been optimized out of the organizational chart and replaced with productivity tools, more efficient communications and a lower ratio of managers to workers. And the actual number of staff required to hit the bottom line has been optimized while CEO salaries have been optimized. If we look a little further down the line, Andrew McAfee's POV is deep on this subject, and more technical than mine.
Industry – We all know that manufacturing was moved offshore en masse over the past three decades to optimize production costs, but several other industry segments have been optimized as well, including Retail which has optimized through consolidation and healthcare which has optimized revenue per patient. Retail has been optimized at a structural level, to provide one-stop shopping for almost everything you need in a single location while volume has been optimized to produce the absolute lowest price and any cost, including optimizing the number of worker hours to keep an optimal ratio of full time to part time employees and save the resulting benefit costs. And it has also optimized the number and variety of retail outlets and small businesses required to service an optimized population in square miles. Healthcare prices have been optimized to take advantage of tax structure, potential law suits, healthcare insurance gaps, maximizing federal matching funds, Board and C-Suite compensation, pharma industry profits, and many more.
Government – Automation has also enabled a profitable business model that optimizes the use of Federal Government funds and ensures that every available dollar is spent, whether it is to make sure everybody gets a state-of-the-art mobile wheelchair, their 120 monthly catheters, a speaking glucose meter, maximum disability benefits, etc. “Don’t worry - we’ll handle all the paperwork.”
Set it and Forget it
The imminent next generation of analytics involves truly “optimized” complex systems with human intervention largely removed from the process. Not to single out Wall Street, but they offer one of the best examples of unbridled application of technology in the singular pursuit of optimization, in their case, profit for themselves and their shareholders. The Financial Services industry has invested billions into technology and employed thousands of physicists and Ph.D.-level mathematicians to achieve a couple-millisecond transaction advantage, and programmed algorithms to use the advantage and change the rules (i.e., share price represents perfect information is no longer true). This has not proved to always produce predictable results, and the ghost in the machine has put us back on the precipice more than once, as seen in this TED video by Kevin Slavin. As we move into a brave new world that combines optimization software with networks that operate too fast for human intervention, more of our lives will be controlled by how rules are programmed into the system than what we do as individuals to impact the results. One of the best examples of where this is heading is the IBM’s Smarter Cities Initiative, which combines intelligent networks that manage Traffic, Water and Electric Utilities, Transportation, Healthcare, Public Safety, Education and others into an overall “Intelligent City”. Everyone hates traffic, so the video example from the IBM innovation site does more to explain this than I can by writing more on the subject.
Whether you agree with it or not, we are on a direct course to this future that is almost impossible to divert. This is a philosophical question and everyone will have their own opinion about the cost/benefit of chasing optimization. Comments and Opinions are welcome, please let us know what you think.
