With an ever changing technology landscape and the overflow of digital data, Business intelligence plays a critical role for companies to remain competitive in the market. The power to understand and analyze data to make quick, competitive and impactful decisions is the need of the hour for any decision maker. BI user adoption plays a critical role in the drive to become a data-driven company. Unfortunately, BI adoption rate for many companies hovers as low as 30% for the executed BI projects. This situation leads to massive loss of time, infrastructure and money spent on these BI projects. Below are a few approaches that help in improving the BI adoption rate in the company.
1) Strategize BI from Top:
Adopting a data-driven culture is a transformational initiative and cannot be started from the bottom rungs of decision making unit. The strategy has to flow from the top to bottom. The corporate objective has to be modularized and the departmental objectives have to be aligned to match to business objectives. Most of the BI projects fail during this phase as companies take the bottom-up approach and the compartmentalized BI implementation eventually does not align with the overall business needs of the organization. Start the business intelligence planning from the top and implement it progressively to the bottom of the decision table.
2) Implementing for business user:
Most BI projects in the market are implemented as packaged solutions with IT department functioning as gatekeepers to the BI reporting. Unfortunately, each business is unique and the business challenges are specific to the organization and there can be no one product fits all solution. Business Intelligence should not to be treated as a replacement to existing reporting environment; rather it should help business users to work smarter, move faster and make better decisions. It has to address to the specific challenges of the company and not just produce template market reports. Eliminating the mindset of treating BI as an IT function and enhancing the business user experience with self-service BI reporting goes a long way in improving the BI adoption rate in the company.
3) Bring BI to review meetings:
While BI is seen as an initiative to enhance the reporting environment and close the gap between data to decisions, it is still not universally accepted tool for review meetings. This situation is partly attributed to limited understanding of the BI audience in the company. While there are power-users in the organization preferring slice and dice of data for dynamic analysis, there are even more information-consumers who would be content with generating static reports for business metrics. Industry estimates a ratio of around 1:4 between dynamic and static reporting. Understanding and balancing the equation between these different types of users is a critical component in the success of BI adoption. Use of BI tool in review meetings helps in collective analysis and thus improving the adoption of BI culture in the company.
These are some of the many steps that can be taken to improve the BI user adoption in the company. The drive has to start with understanding the different stakeholders involved in the decision circle and addressing the specific challenges faced in making decisions.
In the era of digital revolution, decision making has become more of a science than an art. Gone are the days when decisions were made purely on individual skills and experience. With a large influx of data available to all stakeholders of a company, executives and decision-making units are even more accountable for the choices made. The essence of today’s decision making lies in accessing the right information at the right time.
Business intelligence (BI) and analytics are the key to making those informed choices. BI and analytics are witnessing drastic growth in recent years and will continue to do so in coming years as well. The mindset of companies to adapt to the changing landscape of BI and to exploit the benefits that the tools offer to enterprises is a huge challenge for organizations that lived in the ages of traditional reporting and data warehousing.
An aspect that is often observed in organizations is that the business problems are never static. The requirements change time and time again with the new market challenges confronting the company.
The usability factor of the BI data also becomes questionable by the end of a BI project. Thus, business intelligence, which often starts as an initiative to solve a critical business equation, tends to become just another investment in technology by the end of the project.
BI tools have caused a paradigm shift in report viewing and handling. The dynamic capabilities of BI tools are difficult to visualize for companies that used traditional static reports earlier. Hence the real challenge for executives while migrating to BI is ensuring the completeness of the requirement at the beginning phase of the project. This challenge is further enhanced when technology cost is brought into the equation.
A few questions that loom large among executives while dealing with BI projects are:
- What if the solution does not solve the business problem despite matching the requirements?
- How would I be able to convince myself and other stakeholders on the investment made?
- What if the requirements are wrong? How would I avoid a change request scenario?
Many organizations define success as meeting the project requirements, time and cost. The real objective and success of the BI project should be to solve the business problem at hand and not the requirements alone. The blatant truth is that most of the data challenges that confront BI solutions are often un-imaginable in the beginning and hence requirements are never complete. Only when stakeholders view the first cut of the end product, true requirements will begin to flow as data table correlations and visualizations start to make better meaning.
The best way to tackle such complexities is through a Reporting-as-a-Service model. The services model alongside an Agile project methodology will help companies tackle the challenges on an incremental basis. The continuous engagement model between vendors and clients will help the client companies to not only scale their normal reporting environment but also to be responsive and adaptive to the latest trends and dynamic reporting capabilities of BI, mobility, analytics and Big Data. Business-focused metrics can be designed and redesigned to produce actionable insights and to meet the exact challenges confronting the company. The Reporting-as-a-Service model won’t just solve the business complexities alone; it will also aid companies in shifting the effort and focus from reporting to decision making.
The true success of a business intelligence strategy lies in realizing it as a business investment rather than a technology investment.