We carry out surveys regularly on how to make the most of our BI and analytics software.
The survey usually focuses on what tools people use, how they use them, what they use them for, how satisfied they are with the software, and the benefits they get from using the software? This survey provides us with very good evidence on which we can base our recommendations.
To answer the leading question, what factors drive the success of analytics and BI for businesses, and what data do we have to support the advice we give.
The first step is how to evaluate or come to a conclusion when selecting software? There are three dominant ways and methods of evaluating software from the survey.
The first is the competitive evaluation. 64% of the survey respondents run a competitive evaluation of multiple tools. They built a long list of interesting tools and narrowed it down into a shortlist that they often run.
15% only evaluate a single tool. So basically, they check whether a tool that they favor is capable of serving their requirements, and 21 % Skipped a formal evaluation.
Our clear recommendation is to run a competitive evaluation, run it with multiple tools and run it with a proof of concept. From the survey data, we observed that’s the best practice approach. Companies that do a single or no formal evaluation do not get to save that much money. They also don’t save that much time; on the other hand, there are a lot that they do not achieve on a single or no evaluation approach
Benefits from BI and Analytics
In the survey every year, we calculate the level of benefits achieved, and we also calculate a business benefit indicator which ranges between 0 and 10. If we break that down, the average figure per evaluation method shows an index of 6.3. Compared to no formal affiliation at 5.1, the average benefits you gain if you do not run a formal competitive evaluation are much lower than when you run a competitive evaluation.
For instance, a business has a favorite tool, and they decide not to run an evaluation because they have software that functions for them. We advise that they refrain from such acts and perform a thorough evaluation because only a competitive evaluation will help you to determine the most beneficial tool for your business reliably, and only if you find the best tool for your business can you run the best analytics, run the best projects and get the best insights needed.
What Criteria Influence Our Chances of Success with Analytics and Bi
There are two things to look at on criteria that influence a chance of success with analytics and BI.
Criteria That Influence Most Buying Decisions
Under influences, the number one that’s most often considered is the ease of use for consumers. How does the software look? Is it intuitive? Second is the flexibility of the software. How well-equipped is the software to support you in different use cases? How many different use cases can it be used for, and how quickly can it be adjusted? How versatile is it in general? Lastly, the price-performance ratio, it’s no big surprise that the price plays an important role when selecting a software.
Criteria That Yield the Highest Benefits
First is large data handling capacity. How well is the tool equipped to accommodate more and more incoming data? To have software that can support your current and future needs, you need software capable of accommodating a fast inflow of data. The second is fast query performance, closely related to large data handling capacity. You want answers to your data questions very quickly. You want to have a fast response all the time because the number of users will grow, the data volume will grow, and you have to ensure that the queries run fast. Lastly is the high innovative capacity of the vendor. Managing to stay ahead of the competition or close to the competition requires a solid platform where new features and functions can be implemented. If you see very Innovative vendors today, then it’s because they are in the position to do that because they’re using a solid platform that enables them to be Innovative in the future.
Time of implementation
Time of implementation is a major contributor to the success of your analytics. How long did it take from the initial setup of the software until the deployment of the first increment down to the rollout of the first application used in production?
Companies that manage to go all the way within a month-end up with 69% of users saying we are very satisfied with the product that we use. From one to three months, it’s 65%. From one to two years, it’s 28 percent, and it gets as low as 22 percent for three or more years. There is a tendency here, the faster you implement new applications and the faster you deploy them to your customers, the more satisfied the users are.
That raises the question of if I have more time to implement, why aren’t the uses more satisfied? With more time, I can implement more functionality and more features, but why aren’t the users more satisfied? In a very volatile market where customer behavior changes quickly, your competitors attack your market shares from different angles and do that all the time. Then you need fresh insights for making better decisions. You need sound evidence; you need data to be relevant, which needs to be fresh.
In a volatile market, the customers change constantly, the business model changes, your competition changes, and so needs your analytics. You need to change your analytics quickly to serve relevant information to your decision-makers to your managers constantly. If you achieve that, then you can be ahead of your competition. If you don’t achieve that, then you may lag. Suppose you have very long-running projects, one year, two years, and three years in analytics. In that case, you will never be able to accommodate the needs because, within one year, some of the requirements may already be obsolete. With requirements are pouring, running projects for extended periods is often difficult to accommodate, and then the satisfaction drops sharply.