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I recently led a BI tool selection project for one of our customers that is classified in the small and mid-sized business (SMB) market. A business with 100 or fewer employees is generally considered small, while one with 100-999 employees is considered to be mid-sized. (by this definition, our customer would be mid-sized) Having recently heard a number of the enterprise BI vendors state that they are now targeting this market, I figured that they would be prepared for the differences that these customers require with regard to the sales process. Unfortunately, in most cases I didn't find this to be true.
The SMB customers tend to differ from larger, "enterprise" customers in a number of ways. First, they generally have fewer IT employees to support the organization and if a BI competency center exists, it may only consist of one or two resources. Second, the user base is obviously smaller along with the budget for new software. Third, the projects tend to be shorter, including the tool selection process, so the sales cycle is generally faster. At least one of these areas seemed to cause problems for all the vendors on our list, while a few of the vendors seemed unprepared for all these differences.
The selection team's first challenge was in getting some of the sales reps to participate. While a few of the vendors had specific sales reps assigned to the SMB market, my guess is that they primarily focus on the upper end of the market. A sales rep for one of the top enterprise BI vendors, who I won't mention by name, declined to participate unless we agreed to purchase their ETL tool along with their front-end BI tool set. In one case, we discovered that the vendor doesn't sell into SMB customers but instead relies entirely on consulting partners for this area of the market. This works well unless there is no opportunity for the partner to sell consulting. Three of the sales reps wouldn't respond to the RFI before being promised multiple fact gathering meetings. While most sales reps would argue that this is sales 101, unfortunately a faster sales cycle means fewer chances to meet prior to completion of the RFI. Maybe that is taught in sales 102.
Another area the selection team found to be a challenge was with regard to pricing. Most of the vendors claim to have special pricing for SMB customers, but only with regard to the discount. As far as the selection team could tell, the list prices were the same, it was only with regard to the discount amount that the sales rep could provide. This made it difficult to determine whether a tool set was within the budget of the customer until well into the process. The other challenge we found was with regard to the cost of non-production licenses. (development & test environments) In one case, the cost of the non-production licenses would be more expensive than the production licenses. This was due to the fact that the non-production licenses were priced based on assuming 100 users, with no ability to variate.
I realize that not all sales reps are created equally and in some cases, it's the actions of the rep that reflect poorly on the vendor as a whole. However, for the enterprise BI vendors to be successful in this market, they will need a different approach to selling and an updated compensation model for their sales force. It is not enough to simply focus on pricing, they must also focus on the sales process. Handing the opportunity off to an inside sales team or a consulting partner isn't sufficient. It only signals to SMB customers how they will likely be treated once they buy the product. Also, sending in a sales rep that has no training on selling into a smaller customer isn't sufficient either. Chances are that they will overlook opportunites because they expect the process to be the same as selling into larger customers. The truth is that many of these companies will grow out of the SMB market and become bigger fish in the BI pond.
Steve Dine
sdine@datasourceconsulting.com
How many times have you heard a statistic such as "42% of respondents rate their BI program as moderately successful" or "more than 50% of all BI projects fail"? When I read these types of statistics I often wonder what's behind these numbers. I'd love to be able to drill down directly to the respondents and ask them how they defined success or failure when answering the question. I recently met with a company that asked if I could come in and help make their BI program more successful. Naturally, my first question was to ask them how they define success. Each person in the room defined success a bit differently and meeting turned into a healthy discussion on what constitutes a successful BI program.
As an industry, I believe that one of our big challenges is that we have left the definition of success relatively ambiguous and in some cases, in the hands of the tool vendors. We have done a good job at identifying the general contributors of success, such as ROI, better access to data, number of users, increased quality of data, cost savings, etc. The problem is that these contributors in themselves don't necessarily determine the success or failure of a BI program. For example, how many BI programs are considered a failure because they were 3 months late delivering the initial data warehouse or have less than 5% active users in their company.
As a starting point for discussion, I am going to make a definitive, and likely controversial statement, of what defines success and throw some concrete numbers into the mix. In my experience, there are two components that determines the success of a BI program; reality and perception. Reality can drive perception but perception cannot drive reality. From a reality perspective, the success or failure of a BI program can only be measured its ROI. Why? Because companies are in the business to make money and if they don't, they will ultimately fail. A BI program is an investment that a company makes in hopes of achieving a positive return. With that in mind, I contend that a BI program that achieves a negative ROI over time is considered a failure. One that achieves a 0 to 24% ROI is considered a moderate success and one that achieves a 25% or greater ongoing ROI is considered highly successful. Ongoing ROI is calculated each year that takes into account all increased revenues, decreased costs as well as capital and operational investments.
A quick story from the trenches. A few years back I was the director of data warehousing for a large manufacturing company and each month the CIO used to ask me how many active users do we have of the data warehouse. He believed that the program was failing because less than 40% or our targeted constituents were using the data warehouse. Then our team embarked on a project sponsored by the VP of international sales to identify high growth customers and create a set of targeted analyses and reports for his field reps. Ultimately, he attributed 3% of the growth that year in international sales to the work of the DW team. Our CIO stopped asking how many active users we had and starting asking how ROI we were generating from the BI program.
Some readers than have attended my Lean BI course might be scratching their heads thinking that this conflicts with the first principle, "Focus on Customer Value". In my next blog, I'll discuss how customer value drives ROI and why both reality and perception are important to the success of a BI program and how reality can drive perception. In the meantime, I welcome your feedback.
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