Enterprise leaders say that while big data analytics allows organizations to gain a competitive edge, non-technology related issues can actually derail the benefits accrued
While Big data analytics allows business leaders and enterprises to leverage data-driven and real-time insights, helping them to help make informed decisions, customize services/products for better customer relationships, and develop business opportunities, it’s not all fine at the end.
However, these big data strategy initiatives have their own set of hurdles. The interesting part? Most of these hurdles are not technology related! Despite enhancements in the scalability of infrastructure and storage tech that have made it easier to deploy big data analytics, the security of data during transit or at rest is still not guaranteed. And enterprise leaders say that many of the shortcomings are related to trust, the culture of the organization, and skill sets.
Lacking the relevant skills
Leaders say that the biggest challenge faced by them is that most of the data resides in inconsistent, unstructured form, in silos. Collating this data and structuring it is a complicated project. Additionally, most enterprises lack the relevant tools that can enable them to harvest disparate data to build actionable measures, largely because of evolving technology and hence new solutions.
As a result, enterprises are left facing a shortage of relevant and adequate solutions and find it difficult to hire the required resources with appropriate analytical skills. The high cost of taking in experienced data scientists and data engineers is also a disadvantage, to add to the issues.
Lack of trust factor
Enterprise leaders acknowledge that most of the C-suite executives are wary about trusting the utilization of analytics in the enterprise. CEOs are more open to adopting these practices as compared to Directors and the Department Heads. The same practice has been observed at a global level.
Presence of an expert mindset
CIOs say that an unexpected challenge they faced while trying to deploy big data analytics led initiatives, was creating a data-fueled culture in their enterprise. Big data strategies need enterprises to work in a data-based environment.
It proved to be challenging as most enterprises believe in, and work with an expert mindset. Adjusting to a learning-based mindset is a challenge for most enterprises due to the something a simple but widely prevalent- as resistance to change.
Build a business-first big data policy
CIOs say that an enterprise will stand to gain advantages from the implementation of big data analytics despite the challenges. There are no doubts that big data and analytics will play a critical role in creating and even driving the digital economy.
To gain a competitive edge, leaders will be required to manage and successfully harness the data they have. To achieve this, organizations and CIOs must build a business first strategy for any big data initiative that is being considered in the enterprise. In any case, the final goal is to decrease operational costs, mitigate risks, and boost revenue.
Organizations are often aware of the possible advantage areas and potential use cases; however, they lack the data to prove their claims. In such scenarios, they must detect appropriate use cases and initiate smaller projects that help them create value backed by data.
Post that, they can replicate the knowledge for implementation in other use cases. Success relies on appropriate tools, and so enterprises need to rightly select the tools that will prove to be useful in achieving the business goals.