You don’t need to be a scientist to boost your business with applied mathematics
On 22/9/09 SPSS Inc. announced a new certification process to confirm an individual’s expertise with some of their statistical solutions. “Look at this”, I thought “sophisticated software still requires experts to unfold the value they can provide”. Being a physicist by background, I like it how applied mathematics can improve business. However, not everyone sees beauty in algorithms or is interested in statistics.
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%.
I am so glad that my Information Week article BI in Healthcare is receiving interest and mostly positive feedback. I believe that this is indeed a very important topic to write about, especially considering how behind the times the industry is, and what a unique opportunity we have right now to get it right. We so strongly believe that this is such a critical IT issue and challenge, that Forrester is even bending its own rules slightly – typically all our research is “role” based, not industry based, as we most often find that challenges and requirements by role are almost always very similar across industries. Healthcare and public sectors seem to be a big exception, and therefore, I and some of my colleagues do plan to publish more Healthcare IT specific research. For example, I am currently in the middle of surveying top 30+ BI vendors specializing in Healthcare against 40+ criteria. Stay tuned to the results of this research. And my colleague, Craig LeClair (http://www.forrester.com/rb/search/results.jsp?N=0+11226), is in the midst of conducting research on EMR best practices.
The IT mega vendor acquires the predictive analytics specialist SPSS
On July 28th IBM announced the plan to acquire SPSS, a leading provider of predictive analytics solutions. The acquisition, which is subject to shareholder and regulatory approval, is expected to close later this year and will position IBM as a leading vendor of Business Intelligence in the market.
I just came back from an exciting week in Orlando, FL, shuttling between SAP SAPPHIRE and IBM Cognos Forum conferences. Thank you, my friends at SAP and IBM for putting the two conferences right next to each other (time- and location-wise), and for saving me an extra trip!
Both conferences showed new and exciting products and both vendors are making great progress towards my vision of “next generation BI”: automated, pervasive, unified and limitless. I track about 20 different trends under these four categories, but there’s a particular one that is especially catching my attention these days. It went largely under covers at both conferences, and I was struggling with how to verbalize it, until my good friend and peer, Mark Albala, of http://www.info-sight-partners.com, put it in excellent terms for me in an email earlier today: it’s all about “pre-discovery” vs. “post-discovery” of data.
In my recent BI Belt Tightening For Tough Economic Times document I explored a few low-cost alternatives to traditional, mainstream, and typically relatively expensive Business Intelligence (BI) tools. While some of these alternatives indeed were a fraction of a cost of a characteristic large enterprise BI software license, there were even fewer truly zero cost options. But there were some. For example, you can:
Leverage and use no-cost bundled BI software already in-house.Small departments and workgroups may be able to leverage BI software that comes bundled at no additional cost with BI appliances, database management systems (DBMSes), and application licenses. You can consider using these few free licenses from Actuate, IBM Cognos, Information Builders, Jaspersoft, Microsoft, MicroStrategy, Panorama, Pentaho, and SAP Business Objects for additional functions such as testing, QA, and prototyping. While these few free licenses are just a drop in the bucket in a typical large enterprise BI license requirements, do look around and don’t waste money on BI products you may already have.
I always predicted that Open Source BI has to reach critical mass before it becomes a viable alternative for large enterprise BI platforms. All the individual components (a mixture of Open Source BI projects and commercial vendor wrappers around them) are slowly but surely catching up to their bigger closed source BI brothers. Talend and Kettle (a Pentaho led project) offer data integration components like ETL, Mondrian and Palo (SourceForge projects) have OLAP servers, BIRT (an Eclipse project), Actuate, Jaspersoft and Pentaho have impressive reporting components, Infobright innovates with columnar dbms well suited for BI, and productized offerings from consulting companies like European based Engineering Ingegneria Informatica – SpagoBI – offer some Open Source BI component integration.
However, even large closed source BI vendors that acquired multiple BI components over the years still struggle with full, seamless component integration. So what chance do Open Source BI projects and vendors with independent leadership structure and often varying priorities have for integrating highly critical BI components such as metadata, data access layers, GUI, common prompting/sorting/ranking/filtering approaches, drill-throughs from one product to another, etc? Today, close to none. However, a potential consolidation of such products and technologies under one roof can indeed create a highly needed critical mass and give these individual components a chance to grow into large enterprise quality BI solutions.
I had an amazing client experience the other day. I searched long and hard for a client with flawless, perfect, 100% efficient and effective BI environment and applications. My criteria were tough and that's why it took me so long (I've been searching for as long as I've been in the BI business, almost 30 years). These applications had to be plug & play, involve little or no manual setup, be 100% automated, incorporate all relevant data and content, and allow all end users to self service every single BI requirement. Imagine my utter and absolute amazement when I finally stumbled on one.
The most remarkable part was that this was a very typical large enterprise. It grew over many years by multiple acquisitions, and as a result had many separate and disconnected front and back office applications, running on various different platforms and architectures. Its senior management suffered from a typical myopic attitude, mostly based on immediate gratification, caused by compensation structure that rewarded only immediate tangible results, and did not put significant weight and emphasis on long term goals and plans. Sounds familiar? If you haven't worked for one of these enterprises, the color of the sky in your world is probably purple.
Many years ago as I started researching and analyzing the differences between major BI vendors, one criterion that I always used was whether these vendors ate their own dog food. In other words, did a vendor executive team use the same solutions for data collection, building metrics and dashboards to run their own companies that they also tried to sell to their clients? Those who did tended to score higher in my evaluations.
The same guiding principle is applicable to Forrester: you have to eat your own dog food in order to convince the clients to buy your products and services. Hence, our methodologies, such as Forrester Waves are completely open and transparent (thank you, Doug Henschen, for recognizing this in your recent blog), and we encourage our clients to challenge us on every point made in our Waves.