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Is There a Certain Size Business or Certain Vertical Industry for Which SaaS BI Makes Most Sense?

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Wayne Morris: Is there a certain size business or certain vertical industry for which SaaS BI makes the most sense?

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  • As someone who is enthusiastic about SaaS plays in general, pricing is the issue that forces a lot of companies to just go from adopting a SaaS model to one of hosting something similar inhouse and buying an internal server version of the same. I was in another company where we started using Upshot (now part of Siebel CRM) as a SaaS Sales Force Automation platform back in 2003. When we had 10 licenses, a monthly expense of $500 at $50 a pop Plus startup expenses of about $3000 made sense. But when we needed 25 licenses, the pricing just made hosting the same in-house much more sensible.

    The whole idea of SaaS is lost and companies do risk of losing champions of SaaS BI if they do not work hard on the pricing issue. It' s a simple one but something that can make SaaS BI work or not work for companies. Small to Medium sized companies will do this analysis and follow the logic but larger companies may as well as number of licenses increase.

  • It's not necessarily a question of size or industry, but there are some characteristics where it makes more sense:

    1. In geographically disbursed organizations where maintaining common application platforms is problematic.
    2. Where consistency in reporting content, timing or format is a requirement and where the local business environment may lead to inconsistency in interpretation.
    3. Where there is a requirement for compliance to standard policies and/or regulations in reporting and information archiving.
    4. In environments where centralized control is desirable - e.g., control over independent sales force, or outsourced process/production environments.
    5. Where greater agility in enterprise organizational structures is desired and/or anticipated.

    A good example is in large Insurance and Financial Services firms where all of these factors can come into play.

  • Traditionally the thought has been that smaller companies or business units within enterprise environments that want independently driven applications are most likely to adopt SaaS. Many times this may be the case based on time to implement and low overhead costs. However, much adoption also comes from companies that are already used to deploying SaaS based solutions. For instance, companies using Salesforce or ADP, etc. may be more likely to adopt additional SaaS applications because they are used to interacting with their applications this way.

  • I think SaaS BI has a role to play in organizations across industries and of various sizes. Every organization has a set of business functions (Finance, Marketing, Operations, Sales, Strategy etc.) each with its own characteristics that dictate the business decisioning requirements. The applicability of SaaS BI is more a function of these characteristics than the organization themselves. That the characteristics themselves might be dependent on the industry or size is definitely a valid argument but I will leave that for another discussion.

    For example, certain business decisions require a tightly coupled information chain (from ERP to DW to Reporting) and this is best served by in-house / on-premise BI platforms. On the other side of the spectrum, certain decisions are to be taken based on a loosely coupled information chain and these decision makers would be well served by on-demand / SaaS platform.

    Bottom-line, I expect, every organization, big or small, to have a mix of on-premise and on-demand BI platforms each serving a specific business community and opportunity.

  • Choosing between SaaS and On Premises deployment for business Applications such as BI is not a straight forward call as pointed out by the various people of this thread. At GetApp.com we actually try to offer some help to better understand the various aspects to take into consideration before making the right decision. We have developed a free online tool which should help ask yourself the right questions and get some guidance: http://www.getapp.com/personalized_assessment Feedback is welcome as we intend to incorporate more collective intelligence into the tool.

  • At GoodData we see some clear patterns with SaaS BI adoption. It doesn't really break down cleanly into verticals or company size, but in these three ways:

    New data: companies aren't using SaaS BI to look at the same ERP and operational data - they are using it primarily for customer analytics - all the data that surrounds customer interactions, in their CRM system and elsewhere. A lot of this is already in the cloud.

    New users: SaaS BI isn't for the same small group of analysts or BI experts. It's for everyone in sales, marketing, support and services that want to understand the 'story behind the numbers' -- for many companies that means metrics being pushed to users through embedded dashboards in Salesforce and other systems.

    Higher velocity: The data that surrounds customer interactions changes daily (or hourly if you look at web analytics); and the use cases for effective BI are fluid as well. The 'single-version-of-the-truth' approach is not optimal for businesses trying to see patterns in customer analytics. This is a different velocity than the traditional BI approach. Projects have to be realized in days or weeks and not months.

    -Sam at GoodData

  • Though it makes sense for some businesse more then others; I think its more about what problem are we trying to solve by applying SaaS BI as the solution versus a particular industry or business size.

    For SMBs its the cost of entry, potential of lack of technical resources, or removing repetitive process in the creation of a daily Excel report.

    For larger organizations it may comes down to their willingness to adopt SaaS BI, or applying it to a problem where it will add value at minimal cost; I've seen where IT organizations use SaaS BI as a BI for BI or monitor usage on other solutions.

    What I have seen is more of a focus on low hanging fruit versus sticking the square peg in a round hole that many solutions fall for; with the message being presented by the SaaS BI vendors. In cases where the data volumes might be to excessive or security concerns/data restrictions it doesn't make sense to evaluate SaaS BI as the solution at this point in time.

  • Wayne: Companies of all sizes sign up for Zoho.

    Nari: Your example is a good one! At Zoho, we make sure that our SAAS apps are affordable for all. Made a blog post recently of how much Zoho will cost for SMBs - http://bit.ly/8XcYyz

  • The only way to make SaaS enabled BI offering work is to move data on the cloud – which may be seen as a challenge. If data is very confidential, or there are strict regulations for data access, then enterprises would be hesitant to move the data on the cloud. Hence for verticals like banking, financial services - SaaS BI calls for potential risk. Whereas SaaS enabled BI offering is a good proposition for data about marketing, CRM and web statistics which can be easily moved to cloud.

  • I think SaaS BI is very much suited to smaller and medium sized enterprises. Here are some reasons why.

    1) Small and medium-sized businesses often cannot justify the large CapEx of traditional BI, do not have the IT resources to run an on premise database and server system and are not sure that they have the breadth or depth of data to warrant such a system. Often their needs change and evolve far faster than software is developed and installed. SaaS payment structures mean that you have no CapEx and only pay for the amount you use the product. If half your users find they they aren’t deriving any value from the software, they can easily cancel their subscriptions at the end of the month, halving the cost.
    2) Traditional BI demands technical expertise both to manage and use. Business users could not quickly perform analysis themselves; queries had to be made through the IT department and often involved long delays. As there is no software to install, there is no daily maintenance or routine tasks to be done, so nothing to require extra IT hands or expertise. This frees IT professionals to concentrate on strategic IT and growing the business.
    3) With traditional BI having enough data to justify the BI spend is certainly a problem. The huge upfront costs and time investment often cannot be justified by the need for a couple of key decision makers to analyze a small number of records. SaaS BI gets rid of this problem as it provides fully functional BI suite available for just one person. SaaS applications can be rapidly scaled up or down as your business needs change.
    4) Most SaaS products are lightweight and designed to complement the investment in data storage and manipulation that you already have. For example, Bime, a SaaS BI solution, plugs directly in to online and traditional sources to extract data, then allows creation of visualizations and dashboards with a few clicks.

    BI products have traditionally required huge upfront costs, had long lead times and demanded technical expertise to use. SaaS allows powerful functionality without the need for any of these, making it a highly profitable investment for SMBs. This isn’t to say that large enterprises cannot benefit from SaaS BI too. Within departments or teams, larger organizations are deploying SaaS BI more and more as they realize its potential.

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