Every year, hundreds of businesses contact Software Advice to find the best business intelligence software to fit their needs. These interactions with prospective buyers provide us with considerable insight into the broader BI software market and the trends that occur within it.
We recently analyzed a random sample of these interactions to better understand the factors that influence BI software buyers’ purchasing decisions. These findings will help guide the decisions of other buyers in the market for such a solution.
- Most potential buyers sampled are new to BI, with 81 percent stating they have no existing solution in place.
- Business growth rendering existing software inadequate is the most common purchase driver, cited by 46 percent of potential buyers.
- Dashboards are in huge demand, cited by 89 percent of buyers as their most desired functionality.
- Despite industry hype, predictive analytics functionality is requested by just 10 percent of potential buyers in our sample.
- Interest in BI tools, once limited to the enterprise, is now strong among small and midsize businesses (85 percent of buyers surveyed).
The business intelligence market in 2015 is in a state of flux: According to Gartner, it is undergoing a “fundamental shift” as business users demand access to dynamic data analytics tools. This represents a move away from more traditional BI models, which require heavy involvement from a company’s information technology (IT) department.
Investors are also excited by opportunities in BI. In fact, a recent study on venture capital funding in Software-as-a-Service (SaaS) finds that “BI, analytics and performance management” has received more investment than any other market—and more than twice as much as its nearest competitor, customer relationship management (CRM).
Clearly, interest in BI is booming. But what is fueling this interest at the day-to-day business level? In this report, we combine analysis of Software Advice’s own data with interviews with experts in the business intelligence software market to explore pain points, purchase drivers and trends.
81% Don’t Have Business Intelligence Software
When asked about their current software, only one-fifth of prospective buyers in our sample say they already use dedicated BI software in their business. Clearly, there is a large and motivated market of individuals newly curious about the possibilities of business intelligence.
Prospective Buyers’ Current Methods
Businesses without BI solutions are still performing analytic and diagnostic tasks with their data, of course, generating reports and evaluating key performance indicators (KPIs). However, they may do this with Excel, through their own custom systems or, as Hannah Lincoln of data service firm ITAS points out, via the tools built into CRM or enterprise resource planning (ERP) software platforms.
For instance, Lincoln says, “Most ERP packages these days come with some form of business intelligence/reporting software. [With] a little creative thinking, most small businesses can get what they need.”
However, in today’s environment of rapid change and proliferating data, the complexity of the information available can quickly become unmanageable. By the time most buyers speak to Software Advice, they have already decided they want to expand their understanding of their business (or what they can achieve through basic tools) to explore the possibility of gaining deeper insights from data using a sophisticated business intelligence software system.
Indeed, according to Eldad Farkash, founder and CEO of BI and analytics firm Sisense, maximizing the value of a company’s data in today’s business environment is vital and may even be “a matter of survival.”
Farkash points to advertising technology and marketing companies as examples of businesses where “every department needs to get its hands on analytics in real time to survive and grow.” In these contexts, he adds, “waiting hours, days or weeks for data to be analyzed is a luxury they can’t afford.”
But what specific pain points are driving this turn toward heavy-duty data exploitation?
Outgrowing Existing Software Is Main Driver of BI Adoption
We roughly divided buyers into two categories: those who are trying to move towards a hopeful future of improved data use, and those trying to move away from an already existing scenario of data chaos.
In the chart below, the 46 percent of buyers who feel they have outgrown the tools they are currently using belong to the first category. These are largely first-time BI software buyers who frame their need positively: Their business is growing, the amount of data they collect is increasing and they want to invest in tools that will help them optimize their use of that data. Their decision to invest in business intelligence software is proactive and anticipatory.
In the same category are the 33 percent who want better visualizations. Their existing solutions may be usable, but they’re seeking an upgrade so decision-makers can better “see” the workings of their businesses, and thus improve decision-making.
Top Reasons for Evaluating New Software
And then there are the 29 percent in search of a new system. Here the sense is not so much that the company is growing, but that it has already grown to a level where the amount of data has become unmanageable.
As the director of a large health care organization tells us: “We have a hundred facilities around the country and there’s not a standard.”
According to Southard Jones, VP of product strategy for BI vendor Birst, this sense of fleeing from an out-of-control data sprawl is not uncommon in enterprise-level organizations; indeed, “chaos” is what these businesses often encounter.
Jones says that in such scenarios, it’s best to take a targeted approach to implementing a BI tool: Focus on one very specific business metric—employee churn rate, for example—and focus analytics on that first.
“That one rapid win changes the mindset around BI [away from], … ‘I’ve got to solve all my data problems.’ Let’s just solve one very specific business problem with data,” he explains.
“Other problems will come up, but if you keep knocking them down, you’ll be surprised what kind of success you can have.”
Similarly, the 16 percent of respondents in our sample who are having trouble using manual methods, such as spreadsheets, should think carefully before purchasing a BI tool, says Steve Palmer, senior VP of global data and analytics at business technology firm Avanade. The root of the problem may be deeper than inadequate technology:
One must enter the BI world with a willingness to look in the mirror and take on the hard stuff. If you are agonizing over spreadsheet sprawl, then ask: “Are you willing to understand how you got there in order to right the wrongs that led you to this spot?”
Steve Palmer, Avanade
Without that honest questioning, businesses may repeat the mistakes that created the chaos in the first place.
Hyped Predictive Analytics Tools Are Still a Niche Request
As for what functionality buyers specifically ask for, it doesn’t necessarily match the hype. Advanced functionality such as predictive analytics may get its own dedicated blogs and conferences, but it is the classic “meat-and-potatoes” applications, such as dashboards and reporting, that are requested most in our sample.
Top-Requested BI Software Functionality
For instance, a full 89 percent of prospective buyers are seeking BI software that features dashboards, while 55 percent want reporting functionality. These are followed by OLAP and ETL, which are also “traditional” BI tools.
The huge demand for dashboards makes sense in today’s era of business user-driven BI, which was identified as a major disruptive factor in Gartner’s most recent Magic Quadrant for BI and Analytics. Instead of waiting for the IT department to prepare reports, today’s savvy BI user demands more autonomy, and wants “data discovery” tools that will allow them to produce their own analyses. As Nina Sandy, director of product marketing at software firm Kofax says:
“Simplified, intuitive interfaces are now the standard expectation for business users, and they look for that in their solutions,” she says. “And the focus has shifted to meeting the needs of the business users—allowing them to be self-reliant.”
However, businesses that are interested in self-service need to exercise caution. The data might still require preparation by the IT department if it is to be fully reliable, says Dr. Rado Kotorov, chief innovation officer at BI firm Information Builders.
“Organizations must implement a data-governance strategy in tandem with other initiatives to ensure the success of self-service BI,” he says. “As more workers rely on enterprise data, companies without data-governance plans risk providing an inaccurate information snapshot that could cripple the business.”
It is a point echoed by Birst’s Jones, who agrees that as BI becomes more driven by the demands of business users, the demarcation lines between functions have become blurred. For instance, buyers need to be aware that dashboards may not just be static tools for viewing reports, but can be dynamic.
“More and more, you see people interacting with the data, [and in that case] it’s more than just a report,” Jones says. “The danger is: Let’s say somebody creates a nice dashboard, but what exactly are you looking at? Can you really trust that data? Where does it come from?” Data still requires a lot of careful preparation if it is to be exploited correctly, he explains.
Jones continues: “If you don’t have some level of centralized, governed data, if that’s not part of your BI strategy, there is definitely a risk [that] you are going to have three people in a room and have three different answers to the same question—or worse, have three people in the room and one answer, but it’s based on the wrong data.”
But if the hype around self-service tools seems justified, when it comes to predictive analytics—also a hot topic—the picture is different: these tools are requested by a mere 10 percent of buyers. However, given that four-fifths of buyers in our sample do not have a dedicated business intelligence software tool in place, it is understandable that they are less likely to invest in a predictive analytics tool.
Sandy suggests that the demand for more advanced tools can depend on an organization’s analytic maturity.
“Data analysis is an ongoing, iterative process, and dashboarding and reporting are great entry points,” she says. “It sets you up to be collaborative, address governance and focus on an enterprise view of data.”
Scale is also a crucial factor, Sandy adds: “Predictive analytics requires the complexity and data volume that just isn’t available for [smaller] organizations.” To get a truly reliable understanding of what the analysis is providing, she says, “complex algorithms have to be managed, leveraged and results understood.”
However Joanna Schloss, BI and analytics expert at Dell, says that data volume is a less important determinant of the need for predictive capability than data variety and complexity, and that SMBs may be missing out:
“SMBs can have just as much complexity, if not more, in their data environment as their enterprise counterparts, so predictive capabilities are just as relevant,” says Schloss.
“Certainly the job of statistical analysis is not something an SMB can just drop on the average analyst, but with proper IT support and the right software tooling, even small organizations can better leverage their data ecosystem to deliver predictive insight.”
SMBs Increasingly Interested in Targeted Software Options
BI was originally a tool used by large enterprises and organizations. Not only did these “big beasts” have plenty of data to play with, they also had the budgets to purchase complex and expensive systems. In 2015, however, interest in BI solutions spans all business sizes:
Prospective Buyers by Company Size
Indeed, 45 percent of the buyers in our sample come from small businesses (defined as under $50 million in annual revenue) while 40 percent come from midsize organizations (between 50 million and $1 billion). A further 16 percent come from enterprises (over $1 billion).
However, while enterprise buyers are generally aware of how much a BI system costs, prospective buyers from smaller businesses often suffer sticker shock. But as Sandy explains, this is not a new phenomenon.
“The concept of BI implementations have scared off a lot of smaller organizations because of the historic time and resource investment required to get an implementation off the ground,” she says.
For smaller organizations that are seriously interested in adopting dedicated BI tools, there are options. Avanade’s Palmer says that for entry-level users, solutions that start small and scale upwards while offering wide functionality, such as Microsoft Power BI, can be a good fit. This also operates on a “freemium” model, offering an entry-level tier as well as paid versions for more advanced users.
IBM’s Watson Analytics is also offered on a “freemium” basis. Drew Baum, solutions specialist at IBM, explains that Watson Analytics is used by everyone from “startups that don’t have any income yet” to “Fortune 10 companies.”
The tool takes structured data, such as that contained in spreadsheets, and analyzes it to find insights and make predictions. The paid tiers can also analyze social media data from Twitter.
However, the problem with using cheaper tools is striking the right balance, says Kofax’s Sandy.
“Organizations still require full functionality, and some of these solutions are either very restrictive regarding data access or functionality, or leave a lot to be desired with upgrades and expansion,” she explains.
Despite potential budget challenges, there are ways in which businesses operating at a smaller scale may have an advantage, says Edwin Miller, founder and CEO of big-data firm 9Lenses.
“Because smaller businesses are more agile by nature, decision-makers have an even greater opportunity to rapidly act on insights gained from business intelligence,” he explains. “With fewer organizational layers to re-adjust and correct, the benefits of BI can quickly be felt throughout the organization.”
Based on the results of our research, prospective BI software buyers should consider the following when evaluating new solutions:
⇒ Organizational maturity. You must learn how to walk before you can run. Firms should focus on mastering core functionality before attempting to solve all data problems simultaneously or adding tools, such as predictive analytics, that may cause information chaos if used incorrectly.
⇒ IT requirements. Even in this era of systems driven by the needs of business users, guaranteeing the quality of data remains essential. Self-service systems may require more support than vendor marketing materials suggest.
⇒ Scalability. Buyers should consider how well a system will accommodate their company’s future growth—both in terms of the number of users that will need to access the system, and the functionality they will require as the company grows.
There are more BI software solutions on the market than ever before—and as freemium solutions show, more and more businesses can now experiment with BI tools before buying (they can also see demos of full-price systems). However, the tools are sophisticated, and correct research and training are essential if the system purchased is to realize its full potential.
The detailed methodology for this report can be found here.
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