In what we saw as an awesome display of moving the bar higher, Evan Goldberg, NetSuite’s CTO, demonstrated in his Keynote Thursday that NetSuite continues to deliver industrial-strength innovations and solutions using tools that are increasingly easy to use, intuitive and particularly well suited to fast-growing Mid-Market companies with global aspirations.
Picking up from a summary paragraph from a 2009 blog post I wrote on NetSuite in a previous life:
“After looking at this demo it will be a little clearer why IMHO this is what the future looks like – all applications will have built in BI and reporting capabilities much stronger than has previously (been available) – without third party BI and lots of integration services – a big differentiator for SaaS vendors that provide this type of visibility as a standard component of their value proposition.”
- Collaborative Innovation Blog post, April 4, 2009
Among others, there are two things that seem like very good strategic moves for NetSuite: Fishing where the Fish Are, and being in a unique position to leverage the new Enterprise Applications Platform for companies that are ready to expand into global markets.
Fishing where the Fish Are
NetSuite positioned itself from the beginning as an Enterprise Software company, starting with ERP and then building other complex, traditionally on-premises software applications into the platform as successive SaaS waves hit the market and customer acceptance increased; Customer Relationship Management, Supply Chain Integration, Customer Service, Professional Services Automation – all tightly coupled with Billing and Fulfillment for a truly integrated workflow that almost covers the gamut of the Traditional Multi-user Systems requirements (Integrated Front and Back Office). Now adding deeper focus to e-Commerce, Global Financial Reconciliation and Industry Vertical implementations, NetSuite can enable Mid-Market firms to be truly competitive in a global market; leveraging speed and agility to outperform larger slower companies.
We have seen a very steady increase in the willingness (and need) for SMBs to embrace Cloud Computing and SaaS Models that move them out of the annual cycles and cost-center mentality that used to define IS Departments. A good indicator of this is how eager the SMB Channel is to offer a wide range of products and services and here we have seen amazing growth; even from last year to now surveys show the laggards are rapidly jumping on board, as seen in this table:
Of the 615 US-based SMB Channel partners interviewed, 86% were now offering or planning to offer Cloud-Based Services, those Not Planning to Offer Cloud dropping from 38% to 14% of the channels. This data represents aggregate results for VARs, SIs, MSPs, SPs and ISVs. In addition to Cloud Services fast growing areas for the SMB Channel include Mobility Solutions, Managed Services and a wide variety of applications in all three of these categories.
SMBs are Hungry for Enterprise-Level Capabilities
Based on early success in SaaS and basic Cloud Services such as Email, Storage, Back Up and Recovery, and CRM/SFA, Small and Medium Businesses have seen the light at the end of the tunnel. Security, availability and usability objections have been overcome and the cost to implement with lower complexity and higher focus on the core business have resulted a very compelling value proposition in widespread adoption worldwide.
To survive in an increasingly globalized and optimized business environment, SMBs need to be growing faster than the market and their competitors, reflected by their Priorities: #1 Increasing Revenue (56%), #3 – Increasing Productivity (34%), #4 – Penetrating New Markets and Customers (32%), and #6 – Speed to Market / Keeping Pace with Competition (28%). On the other hand, rapid growth without an increase in efficiency is unsustainable, so the rest of the priorities revolve around scaling the business efficiently; including #2 – Reducing OPEX (45%), #7 – Collaborating Efficiently (29%), and Reducing Cost of IT (27%).
Because Cloud Computing has been able to deliver these benefits much more effectively than the previous generation of Client/Server architecture did, SMB customers report between 75-80% satisfaction levels of “Satisfied” or “Very Satisfied” with their Cloud-based implementations.
All of this bodes well for NetSuite as the market matures and moves further into the cloud looking for Enterprise-Level capabilities. And timing is also very good as we can see from the additional results of the 2013 SMB Channel Partner Survey:
For Channel Partners Offering or Planning to Offer Cloud Services (85%), the left column shows the top 12 applications cited by Partners based on currently offered Cloud Applications, the middle column represents Cloud Applications that Partners plan to offer this year, while as the title suggests, the “No Plans” column shows the share who say they have no plans to offer the Application. It is pretty clear that the areas of focus and strength for NetSuite are lining up with the opportunity, or put in another way, the Mid-Market needs are maturing to a level that can benefit from NetSuite’s focus. And while there are many companies in the market who can provide these as point solutions, there are very few who can provide them in a unified suite of applications, with an integrated group of cross-department KPIs that can be used to get at a single version of the truth.
In terms of product coverage and timing, we feel the rapid adoption in the Mid-Market towards Cloud Infrastructure, successes in overcoming basic Security, Functionality and Availability concerns and the need for Mid-Market customers to grow rapidly and efficiently, all support NetSuite’s strategy and roadmap as presented at the conference, providing a lot of runway for the next few years.
Leveraging A New Enterprise Applications Platform
The second major point is that by building their platform from the very early days of the Internet as a transaction platform NetSuite has been able to been able to take advantage of both technology and market advances. In 1997, the critical weakness of the Internet was that while it was very good for moving brochureware around the world quickly, more mature applications that required a lot of integrity and accuracy – such as OLTP in Financial Reconciliation and Supply Chain Integration – were not reliable enough; the Databases, Middleware and Network Management needed to improve and there was a serious shortage in programmers who could do this kind of heavy lifting.
Fast forward five years and the dotcom bust had made commercial broadband access ubiquitous and the tools and skills had (almost) caught up to the hype. CRM, the Killer App was being brought online to the SMB community through SalesForce.com and the benefits of a SaaS model were becoming very clear, albeit with some remaining hiccups and most enterprises waiting on the sidelines for critical applications.
NetSuite started with one of the most difficult challenges back in 1998; ERP Applications with all the Enterprise-level OLTP and Database Management challenges that came with them. By doing this, the ability to grow an integrated set of applications using a single foundation, has paid off in terms of functional leadership. Others in the market, most notably SAP for Back Office and Oracle for Front Office, have taken an “Acquire and Integrate” approach, which is complicated and time consuming in comparison. The fact that NetSuite has survived and thrived in this environment is testament to vision, determination and execution.
Without getting too abstract, we see long term patterns in the software market that seem to ring true over time – the first is to win a narrow space, shore up the position, look left and right and take the adjacent space that is most lucrative and easy to assimilate (by hook or crook). Repeat. The second is that network effects rise in proportion to the number of users: Market Share is King. The third is to focus on the Scalable model and ensure to develop an ecosystem of partners who can add value profitably. Finally, at a very abstract level, the history of IT has been a steady, long march to Data Integration for Process Automation and Optimization. Whether you call Big Data, Distributed Database Management, Supply Chain Integration, Enterprise Performance Management or Google Search, it boils down to integrating disparate data and making it useful for decision making, with a relentless concentration on efficiency. As seen in the Business Intelligence segment, those who started with an Internet-based implementation approach rather than one of everything to every mapping, have ended up with an easier road to implementation; consider Siebel vs. SFDC, SAP vs. NetSuite, BoA Merchant Banking vs. PayPal, or Cognos vs. Domo. New, better tools and focus on specific data integration points rather than mapping every possible permutation of interaction between systems has resulted in faster time to value, less complexity for the channel and much less risk for customers. Breakthroughs such as scalability with Multi-Tenant Architecture have also resulted from solving the problem from a clean slate.
In our 2012 SMB 2020 Technology Report, we described our perspective of the IT Environment of the future, Client, Server and Network. This graphic shows a functional view of the Multi-user System, traditionally called the “Server” within a Client/Server Architecture. This view has CRM as the Hub component, surrounded by an increasingly integrated suite of Applications areas that eventually cover the complete information requirements of the Front and Back Office to run the business using a highly customized group of integrated KPIs. This type of integrated Nirvana has been an objective for a long time; however, it seems to be closer, clearer and much less complicated than it used to be when looking at the NetSuite Roadmap, i.e., we are not counting the dozens of modules that need to be installed, configured and integrated (and who is responsible to manage it). NetSuite’s rapid increase in large customers and decision by the traditional big Systems Integrators to jump on board seem to indicate that timing is good and the functionality is there.
Channel Implications
As the functionality and capabilities of the platform have changed with Cloud Computing, so have the dynamics of the Channel, especially in the Small and Medium Business space. Access to capabilities that were previously far out of the reach of SMBs has fueled the adoption of increasingly complex applications. Ironically, the benefits of the SaaS architecture have compressed and digitized the sales process, allowing companies to sell directly through an online channel, with demand generation, research, pre-sales, sales demonstrations, etc., conducted through inbound sales organizations rather than relying on channel partners to push products and services to the market. The proliferation of horizontal SaaS applications, such as email, webinars, Storage and Back Up has spawned a generation of self-configured apps that have made the customers question the need for third party involvement. It has also shorted the decision cycle substantially; many times cutting the channel out completely and giving rise to a “trusted advisor” role, especially in the lower Mid-Market.
Our research has shown that generally the more complex a solution, the more likely it is to have a partner involved in the implementation. Because NetSuite offers relatively complex solutions, it will have to play on both sides of the fence here – avoiding conflict with large partners for direct sales and providing profitable opportunities to the SMB channel partners, this was one area we felt might be a yellow flag in the distance.
Mobility is coming on Strong
With the installed base of Tablets and Smartphones exceeding that of PCs this year and annual sales of the former expected to number in the hundreds of millions higher by 2018, we see a fundamental shift in the way customers access and manipulate data. “Fundamental” meaning the difference between double-entry ledger accounting in physical books to a software application or the move from IBM Selectric Typewriter to PC-based Word Processing applications; nothing will ever be the same, and it is inevitable. There has already been a steady stream of casualties in the wake of Smartphone sales – single function GPS devices, midrange Digital Cameras and landline phone sets have all peaked in global consumption in the wake of accelerating handset sales. Just as the Internet itself essentially changed all business where value could be digitized (Financial Services, Travel, Shopping, and Advertising), so will ALL industries change as the primary mode of information consumption to the Internet is by mobile device.
This is the area that saw the greatest change in our 2013 SMB Channel Survey, from 56% of partners who said they were not planning to offer Mobility solutions in 2012, the number dropped to 8% this year, representing a doubling of Mobility Solution partners in the market as they implement the plans.
We did not hear that much about mobility from NetSuite during the conference, but given their strength in operational visibility through dashboards across departments, we think focus on this area could help both channels and end users.
Techaisle Blog
Many organizations are starting to think about “analytics-as-a-service” (no acronym allowed) as they struggle to cope with the problem of analyzing massive amounts of data to find patterns, extract signals from background noise and make predictions. In our discussions with CIOs and others, we are increasingly talking about leveraging the private or public cloud computing to build an analytics-as-a-service model.
The strategic goal is to harness data to drive insights and better decisions faster than competition as a core competency. Executing this goal requires developing state-of-the-art capabilities around three facets: algorithms, platform building blocks, and infrastructure.
Analytics is moving out of the IT function and into business — marketing, research and development, into strategy. As a result of this shift, the focus is greater on speed-to-insight than on common or low-cost platforms. In most IT organizations it takes anywhere from 6 weeks to 6 months to procure and configure servers. Then another several months to load configure and test software. Not very fast for a business user who needs to churn data and test hypothesis. Hence cloud-as-a-analytics alternative is gaining traction with business users.
The “analytics-as-a-service” operating model that businesses are thinking about is already being facilitated by Amazon, Opera Solutions, eBay and others like LiquidHub. They are anticipating the value migrating from traditional outmoded BI to an Analytics-as-a-service model. We believe that Amazon’s analytics-as-a-service model provides a directional and aspirational target for IT organizations who want to build an on-premise equivalent.
Situation/Problem Summary: The Challenges of Departmental or Functional Analytics
The dominant design of analytics today is static or dependent on specific questions or dimensions. With the need for predictive analytics-driven business insights growing at ever increasing speeds, it’s clear that current departmental stove-pipe implementations are unable to meet the demands of increasingly complex KPIs, metrics and dashboards that will define the coming generation of Enterprise Performance Management. The fact that this capability will also be available to SMBs follows the trend of embedded BI and dashboards that is already sweeping the market as an integral part of SaaS applications. As we have written in the past, the move to true mobile BI can be provided as an application "bolt-ons" that work in conjunction with an existing Enterprise Applications or as pure play developed from scratch BI applications that take advantage of new technologies like HTML5. Generally, the large companies do the former through acquisition with existing technology and integration and with start-ups for the latter. Whether at the Departmental or Enterprise level, the requirements to hold down costs, minimize complexity and increase access and usability are pretty much universal, especially for SMBs, who are quickly moving away from on-premise equipment, software and services.
After years of cost cutting, organizations are looking for top-line growth again and finding that with the proliferation of front-end analytics tools and back-end BI tools, platforms and data marts, the burden/overhead of managing, maintaining and developing the “raw data to insights” value chain is growing in cost and complexity - a balance that brings SaaS and on-premise benefits together is needed.
The perennial challenge of a good BI deployment remains: it is becoming increasingly necessary to bring the disparate platforms/tools/information into a more centralized but flexible analytical architecture. Add to this the growth in volume of Big Data across all company types and the challenges accelerate.
Centralization of analytics infrastructure conflicts with the business requirement of time-to-impact, high quality and rate of user adoption - time can be more important than money if the application is strategic. Line of Business teams need usable, adaptable, and flexible and constantly changing insights to keep up with customers. The front-line teams care about revenue, alignment with customers and sales opportunities. So how do you bridge the two worlds and deliver the ultimate flexibility with the lowest possible cost of ownership?
The solution is Analytics-as-a-Service.
Emerging Operating Model: Analytics-as-a-Service
It’s clear that sophisticated firms are moving along a trajectory of consolidating their departmental platforms into general purpose analytical platforms (either inside or outside the firewall) and then packaging them into a shared services utility.
This model is about providing a cloud computing model for analytics to anyone within or even outside an organization. Fundamental building blocks (or enablers) like – Information Security, Data Integrity, Data and Storage Management, iPad and Mobile capabilities and other aspects – which are critical, don’t have to be designed, developed, tested again and again. More complex enablers like Operations Research, Data Mining, Machine Learning, Statistical models are also thought of as services.
Enterprise architects are migrating to “analytics-as-a-service” because they want to address three core challenges – size, speed, type – in every organization:
- The vast amount of data that needs to be processed to produce accurate and actionable results
- The speed at which one needs to analyze data to produce results
- The type of data that one analyzes - structured versus unstructured
The real value of this service bureau model lies in achieving the economies of scale and scope…the more virtual analytical apps one deploys, the better the overall scalability and higher the cost savings. With growing data volumes and dozens of virtual analytical apps, chances are that more and more of them leverage processing at different times, usage patterns and frequencies, one of the main selling points of service pooling in the first place.
Amazon Analytics-as-a-Service in the Cloud
Amazon.com is becoming a market leader in supporting the analytics-as-a-service concept. They are attacking this as a cloud-enabled business model innovation opportunity than an incremental BI extension. This is a great example of value migration from outmoded methods to new architectural patterns that are better able to satisfy business’ priorities.
Amazon is aiming at firms that deal with lots and lots of data and need elastic/flexible infrastructure. This can be domain areas like Gene Sequencing, Clickstream analysis, Sensors, Instrumentation, Logs, Cyber-Security, Fraud, Geolocation, Oil Exploration modeling, HR/workforce analytics and others. The challenge is to harness data and derive insights without spending years building complex infrastructure.
Amazon is betting that traditional enterprise “hard-coded” BI infrastructure will be unable to handle the data volume growth, data structure flexibility and data dimensionality issues. Also even if the IT organization wants to evolve from the status quo they are hamstrung with resource constraints, talent shortage and tight budgets. Predicting infrastructure needs for emerging (and yet-to-be-defined) analytics scenarios is not trivial.
Analytics-as-a-service that supports dynamic requirements requires some serious heavy lifting and complex infrastructure. Enter the AWS cloud. The cloud offers some interesting value 1) on demand; 2) pay-as-you-go; 3) elastic; 4) programmable; 5) abstraction; and in many cases 6) better security.
The core differentiator for Amazon is parallel efficiency - the effectiveness of distributing large amounts of workload over pools and grids of servers coupled with techniques like MapReduce and Hadoop.
Amazon has analyzed the core requirements for general analytics-as-a-service infrastructure and is providing core building blocks that include 1) scalable persistent storage like Amazon Elastic Block Store; 2) scalable storage like Amazon S3; 3) elastic on-demand resources like Amazon Elastic Compute Cloud (Amazon EC2); and 4) tools like Amazon Elastic MapReduce. It offers choice in the database images (Amazon RDS, Oracle, MySQL, etc.)
How does Amazon Analytics-in-the-Cloud work?
BestBuy had a clickstream analysis problem — 3.5 billion records, 71 million unique cookies, 1.7 million targeted ads required per day. How to make sense of this data? They used a partner to implement an analytic solution on Amazon Web Services and Elastic MapReduce. Solution was a 100 node cluster on demand; processing time was reduced from 2+ days to 8 hours.
Predictive exploration of data, separating “signals from noise” is the base use case. This manifests in different problem spaces like targeted advertising / clickstream analysis; data warehousing applications; bioinformatics; financial modeling; file processing; web indexing; data mining and BI. Amazon analytics-as-a-service is perfect for compute intensive scenarios in financial services like Credit Ratings, Fraud Models, Portfolio analysis, and VaR calculations.
The ultimate goal for Amazon in Analytics-as-a-Service is to provide unconstrained tools for unconstrained growth. What is interesting is that an architecture of mixing commercial off-the-shelf packages with core Amazon services is also possible.
The Power of Amazon’s Analytics-as-a-Service
So what does the future hold? The market in predictive analytics is shifting. It is moving from “Data-at-Rest” to “Data-in-motion” Analytics.
The service infrastructure to do “data-in-motion” analytics is pretty complicated to setup and execute. The complexity ranges from the core (e.g., analytics and query optimization), to the practical (e.g., horizontal scaling), to the mundane (e.g., backup and recovery). Doing all these well while insulating the end-user is where Amazon.com will be most dominant.
Data in motion analytics
Data “in motion” analytics is the analysis of data before it has come to rest on a hard drive or other storage medium. Due to the vast amount of data being collected today, it is often not feasible to store the data first before analyzing it. In addition, even if you have the space to store the data first, additional time is required to store and then analyze. This time delay is often not acceptable in some use cases.
Data at rest analytics
Due to the vast amounts of data stored, technology is needed to sift through it, make sense of it, and draw conclusions from it. Much data is stored in relational or OLAP stores. But, more data today is not stored in a structured manner. With the explosive growth of unstructured data, technology is required to provide analytics on relational, non-relational, structured, and unstructured data sources.
Now Amazon AWS is not the only show in town attempting to provide analytics-as-a-service. Competitors like Google BigQuery, a managed data analytics service in the cloud is aimed at analyzing big sets of data… one can run query analysis on big data sets — 5 to ten terabytes — and get a response back pretty quickly, in a matter of seconds, ten to twenty seconds. That’s pretty useful when you just want a standardized self-service machine learning service. How is BigQuery used? Claritic has built an application for game developers to gather real-time insights into gaming behavior. Another firm, Crystalloids, built an application to help a resort network “analyze customer reservations, optimize marketing and maximize revenue.” (THINKstrategies’ Cloud Analytics Summit in April, Ju-kay Kwek, product manager for Google’s cloud platform).
Bottom-line and Takeaways
Analytics is moving from the domain of departments to the enterprise level. As the demand for analytics grows rapidly the CIOs and IT organizations are going to be under increasing pressure to deliver. It will be especially interesting to watch how companies that have outsourced and offshored extensively (50+%) to Infosys, TCS, IBM, Wipro, Cognizant, Accenture, HP, CapGemini and others will adapt and leverage their partners to deliver analytics innovation.
At the enterprise level a shared utility model is the right operating model. But given the multiple BI projects already in progress and vendor stacks in place (sunk cost and effort); it is going to be extraordinarily difficult in most large corporations to rip-and-replace. They will instead take a conservative and incremental integrate-and-enhance-what-we-have approach which will put them at a disadvantage. Users will increasingly complain that IT is not able to deliver what innovators like Amazon Web Services are providing.
Amazon’s analytics-as-a-service platform strategy shows exactly where the enterprise analytics marketplace is moving to or needs to go. But most IT groups are going to struggle to implement this trajectory without some strong leadership support, experimentation and program management. We expect this enterprise analytics transformation trend will take a decade to play out (innovation to maturity cycle).
Shirish Netke
This is the second in a series of BI-related posts and it deals with what platforms are being selected and what objectives are being served with SMB Business Intelligence customers. Despite a much shorter history than packaged BI, our survey found a higher level of Cloud-based than packaged BI applications within the SMB respondent base. You may want to open it up to full size as the charts are a little crowded.
