- log in
Posted by Boris Evelson on September 19, 2009
As many of my readers know, for years I’ve been quite skeptical about non-mainstream BI solutions, such as BI SaaS. Security, control, operational risk, data, metadata and application integration are just some of the requirements for enterprise BI that are still on my watch list as potential reasons to be weary about BI SaaS. However, I am also a very pragmatic analyst and truly believe that nothing but supply and demand drive the markets. And I am now, slowly but surely, beginning to believe there couldn’t be a better case for demand for BI SaaS especially after findings from one of the project that I am currently conducting.
I recently talked to a few dozen non-IT professionals (specifically in front office roles, such as sales and marketing) across multiple industries, regions and company sizes. Guess how many of them fully or partially relied on IT for their day to day operational and strategic information needs? BIG FAT ZERO!!! This finding was a huge surprise to me – yes, I did expect to find something like less then 50% reliance on IT, but I surely did not expect to find 0%.
It is truly amazing that after 30 or so years of BI software, services and solutions vendors and internal IT organizations making a strong push and a case for BI, they are still not even making a dent in the front offices. What are the reasons? Among many others, sales and marketing folks that I interviewed are citing being low on IT priority list (why???), IT not speaking their language, high cost, inflexibility of company standard BI solutions, lag times to roll something out – and the list goes on and on and on.
So what’s a sales or a marketing professional to do? Fortunately, they do have options. I am sure you all know what their option #1 is. Yes, you guessed it – Excel. But while Excel remains and will continue to remain for the foreseeable future #1 BI tool, it does have lots of limitations, and all of the business folks I talked to are looking for something that has more pre-built BI solutions, can handle gigabytes (and eventually terabytes) of data, and is more Web 2.0 and collaborative than Excel. Many BI SaaS vendors indeed provide just that.
Is BI SaaS a panacea to all these issues and challenges? Absolutely not. My concerns cited at the beginning of this blog still need to be addressed. Chief among them is the financial viability and long term survivability of BI SaaS vendors, since most of them are tiny, startup companies. So how do you short list a BI SaaS company and mitigate your risks?
First consider some soft differentiations. While these are hard to verify, and may or may not directly correlate and contribute to ultimate vendor success, these are a good starting point (or ending point, to put the final touches on your evaluation) to begin shortlisting your BI SaaS choices:
- VC backing. Is the firm backed by a VC with good track record in information management space?
- Profitability or loss run rate. Is the business profitable or is the loss rate manageable, predictable and adequately financed till the planned break even / profitability goal?
- Salesforce.com recommendation. Does Salesforce.com (or another major vendor on whose platform, data source, etc analytics are based) provide favorable or unfavorable recommendation?
- Management team. Does the management team have a good track record with successful startups and solid BI experience?
Next, proceed to evaluating hard facts. These have to be easily verifiable, and will most probably directly contributes to the ultimate success of a vendor:
Architecture and technology
- Multitentant architecture. Is the architecture truly multitentant or is SaaS offering really an ASP/MSP under the covers ? In other words, can a customer swipe a credit card and get provisioned instantly without a necessity for any manual intervention, setup, etc? This, by the way, is the main reason why I often exclude mainstream BI vendors from BI SaaS category – but I welcome their challenge to this point.
- In the cloud infrastructure. Is the vendor in the business of supporting servers and DBMS, or is all infrastructure hosted by in the cloud vendors like Amazon or Google? Can the vendor concentrate its efforts 100% on functionality and not infrastructure?
- Salesforce.com dependency. Is the software offering 100% dependent on a single data source? Does the vendor have anything else to fall back on should that one single dependency not work out? Some other typical sources include Netsuite, Quickbooks online, clickstream data from Google, payroll data from Paychex, and others.
- Fixed or flexible data model. Does the vendor provide a very industry or functionally specific data mode, vs. can you build your own data model or both?
- Metadata. Does the tool give you capability to import/export metadata so that business and technical metadata can be integrated and reused with other enterprise applications?
- Data integration. Does the vendor provide simple (flat file) import mechanism, SQL or MDX based import or a full blown ETL procedural/scripting language? Does the vendor automatically infer and build a star scheema or requires you to do the target data modelling?
- APIs, Web Services. Can product functionality be modified, exposed and reused in other applications via APIs or Web Services?
- 11 styles of BI. Does the vendor provide BI functionality to support all 11 styles of BI (8, such as reporting, querying, OLAP, dashboards, etc are listed in my recent BI Wave)?
- Architectural secret sauce. Since any SaaS business is in danger of becoming commoditized does a vendor have a “secret sauce”, a protectable IP that truly differentiates them?
- Are customer references available? From customers in production (not POCs or prototypes)? What is the total number of verifiable customer logos in production? How diverse is this verifiable customer base by industry, enterprise size, function?
- Set up services. Does the vendor offer software and application setup services?
- Integration services. Does the vendor offer broader data integration services?
- Management consulting services. Does the vendor offer strategic, management consulting-type advisory services?
Hopefully, this checklist is comprehensive and practical enough to help you shortlist a BI SaaS vendor that fits your business needs and is less then likely to fail in the near future. However! You still need to mitigate the risk by
- Backing up your own data
- Having a BI SaaS vendor Plan B. Keep track of the other BI SaaS vendors - and be ready to have one of them pick up the business if your current BI SaaS vendor fails.
- Having a commitment from Salesforce.com (or the other appropriate ERP vendor) to support your SaaS analytics in case your BI SaaS vendor fails
- Having your internal IT resources stand by and have a plan and a periodic fire drill on how to take over and migrate your data into the enterprise BI solution
Now that I re-read my blog – I am thinking, why not actually poll all current BI SaaS vendors and have them fill out the above questionnaire and turn it into a research doc? I think I will do just that shortly. The current list that I have includes:
Am I missing anyone?
Search Forrester's Blogs
The dynamics that will shape the future in the age of the customer »
Planning for innovation and risk in the wake of Brexit »
Forrester's CX Index
Predict how actions to improve CX will affect revenue performance.
Measure the customer experiences that matter most »
- Anjali Yakkundi (34)
- Art Schoeller (2)
- Boris Evelson (165)
- Claire Schooley (2)
- Danielle Geoffroy (1)
- Diego Lo Giudice (24)
- Dominique Whittaker (4)
- Duncan Jones (2)
- Gene Cao (1)
- George Lawrie (19)
- Holger Kisker (38)
- Ian Jacobs (13)
- Jeffrey Hammond (31)
- Jennifer Belissent, Ph.D. (2)
- John Bruno (4)
- John R. Rymer (46)
- John Wargo (11)
- Jost Hoppermann (34)
- Kate Leggett (154)
- Kyle McNabb (12)
- Leonard Couture (1)
- Liz Herbert (4)
- Margo Visitacion (9)
- Mark Grannan (12)
- Martha Bennett (13)
- Michael Barnes (21)
- Michael Facemire (21)
- Mike Gualtieri (126)
- Nick Barber (21)
- Noel Yuhanna (10)
- Paul Hamerman (2)
- Philipp Karcher (1)
- Phoenix Zhang (3)
- Randy Heffner (15)
- Rowan Curran (2)
- Stephen Powers (23)
- Ted Schadler (38)