By Tavishi Agrawal on Monday, 07 November 2011
Category: Analytics and AI

SMB Business Intelligence Spend & Adoption: Market Ripe for Growth

Global SMB Business Intelligence spend is estimated to be US$2.9 Billion in 2011, a little more than half of estimated spend by Enterprises at US$5.7 Billion. However, confusion abounds because of proliferation of front-end analytics tools and back-end Business Intelligence tools, analytical platforms, as well as data marts. And now more than ever the need for business intelligence is strong, especially among SMBs as they have to increasingly carry an added burden of managing, maintaining and developing insights from raw data.

Business Intelligence is among Top 5 investment solutions planned by SMBs. The current economic scenario has businesses of all sizes focused heavily on identifying profitable customers to improve the ROI on marketing dollars spent. While a number of SMBs have already deployed formal CRM solutions and many others have internally developed CRM processes, the next focus is on making sense of the data captured, linking it to business objectives and monitoring business performance. Large businesses have over the last decade spent billions in improving data analytics capabilities; however, typical business intelligence solutions have been out of reach for majority of SMBs due to cost and deployment complexity. But there are a host of new entrants in the field that are resetting the price bar and filling the gap between low-end MS Excel based solutions and high end solutions such as SAP Business Objects and IBM Cognos.

For example in the US alone, when Techaisle asked 850 SMBs:
Please tell us which of the following technologies you are either “investing in”, “investigating”, or “Ignoring”; [Investing: Have completed purchase, Post purchase deployment phase; Investigating: researching or in pilot phase; Ignoring: not considered important]


Results below for US SMBs shows that the market is ripe for growth and adoption.



Historically, businesses have used a hub-and-spoke model, that is, an enterprise-level data warehouse with dependent data marts.  But this poses a problem as business intelligence and analytics are required by businesses to have high quality and incredible execution speeds because time-to-market is of essence.

As per Techaisle research, 50 percent of mid-market businesses (100-999 employees) and 53 percent of Enterprises (1000+) say that “Improving effectiveness of sales, marketing and business decision making through investments in data mining & business intelligence solutions” is critical. In such a dramatic scenario it becomes more useful for businesses to utilize a virtual data warehouse that pulls data dynamically from various applications as needed.

Similarly, on a scale of 1-9 where 9 is extremely critical, SMBs rate “Improving responsiveness to changing customer needs” as 6.5. These data points cannot be ignored.

Many upper-mid-market businesses use on an average of 6.1 different types of business intelligence solutions. These could be in-house development or a combination of SAS, IBM-Cognos, SAP Business Objects, Microstrategy, Oracle-Hyperion and several other players that provide point solutions. This leads to unclear KPIs, conflicting dashboards and only few metrics that are actionable. These mid-market businesses are trying to turn to analytics-as-a-service.

It would do well for vendors that are targeting the business intelligence to focus on analytics-as-a-service offering for SMBs. However, a key of aspect of any such solution would be the ability to quickly integrate applications or if not, ability to seamlessly pull data for the stakeholders in an easy to use format.

Tavishi Agrawal
Techaisle

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