What IT leaders Must Know While Modernizing BI Tech Stack
BI & Analytics has got maximum mind-share like never before. Though the advancements and innovation in BI & Analytics space is not new and have been steadily modernized over the past 2 decades, the disruptive innovation of Hadoop and other Big-Data technologies moved BI & Analytics onto center stage. Even conservative business houses and IT leaders started eyeing Analytics in its true sense. They are also having a closer look at adapting latest BI technologies into their stable hitherto served by Legacy applications/platforms. Following Key considerations help IT leaders in this transition.
1. Asses the customer needs
Quite often than not, such transformational programs tend to forget the customer especially if the reporting/analytics applications are a mere data push to the customers. The benefit to the customer should be thoroughly analyzed and quantified. If the organization is just a conduit for data passage and the end-customers already have a well-defined BI strategy and infrastructure in place, then IT leaders should think and quantify the ROI before embarking on any such initiative. However, if IT leaders have a well-defined strategy to harness and monetize the data they can rightly take advantage of the current BI/Big data technologies. Customers buying or partnering such an initiative results faster with higher ROI and increases the success rate of such a program.
2. Resource Assessment
Organizations should assess how modernization affects its capabilities in terms of human capital, hardware and software resources and future utilization of the same. IT leaders should evaluate whether the available resource’s capacity and capability is scalable or not. Also, whether the costs involved in scaling up the human capital will yield the required returns on Investments or not should be thoroughly analyzed. There are numerous examples where organizations had to incur huge losses and reverse their decisions when such a holistic capability assessment has not been taken into consideration. This becomes critical for organizations catering to niche or business domain centric functions.
3. Technology Assessment
One of the key drivers of such a transformational program is to adapt to the globally changing technology ecosystem. It is quite imperative that the technology or platform chosen is based on a holistic assessment of customer needs, organization’s resources (human capital and allied resources) and broader vision to harness and monetize the data. At the same time the software capitalization, scalability and the viability of the platform towards a foreseeable future should be considered. Also, if the organizations or IT leaders are not in the business of providing analytics products or trends with data then IT leaders need to think twice before investing in advanced analytics suites. However, many organizations have products which process data for the customers. They traditionally provide just the control reports or required data dumps to the customers. Those organizations can think of taking advantage of Big Data technologies and the latest trends in BI technologies to provide trends, dashboards, metrics and various analytics products to the customers. This will help the customers make decisions hitherto unthinkable and also opens new vistas of business for the IT organizations. However, this warrants diligence from IT leaders in selecting appropriate technology such as
a. Advanced Data visualization tools
b. In-memory BI tools
c. Self-service BI tools or
d. Pure Dashboard and reporting tools
e. Enterprise BI platforms
f. Open-Source BI tools
g. Latest innovations –Big Data technologies
Another key criterion to be considered is the ease of target technology’s adaptation to the current organization’s infrastructure, Otherwise this causes nightmares and incurrence of huge investments just to make the technology work thus seriously impeding the benefits that can be derived. The only caution is Head should prevail over Heart.
These considerations helps IT leaders to Jump start the journey of BI tool adoption (especially in a green field implementation).As the old adage goes Job well start is half done.
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