While leading companies are banking on big data technologies to tackle the changed reality of the digital age, others find the whole big data bandwagon a little overwhelming. It is no secret that companies generate huge amounts of data, and insights created from this data can lead to several benefits, such as a better understanding of customers, better customer experience, improved marketing effectiveness, higher sales driven by a better understanding of your prospects, and more effective market research.
However, such companies have several concerns before going for the implementation of a big data program. These might dampen a company’s interest in investing in big data.
The following are some of the common concerns companies have when it comes to investing in big data.
Cost of big data program
A big data program is a technology-driven process. Implementing a full-fledged program may incur heavy expenditure. There are three main cost-related factors:
- Cost of technology: This involves the cost of advanced analytics technology which is required to aggregate and process big data.
- Cost of hiring big data experts: This involves investments needed to build a team of big data analysts.
- Ensuring return on investment (ROI): Most big data programs fail when the insights generated do not translate into business actions. So, how can companies ensure that the big data program pays off in terms of business outcomes?
Lack of talent with big data expertise
A big data program requires a team, which understands not only the data but also the technology along with the business. Acquisition and training of such talent involves expenditure in terms of money as well as time.
Poor quality of data
The quality of insights generated from a data set directly depends upon the quality of the data itself. Big data would render itself useful only when it does away with all the clutter that inevitably comes with it. Stale, irrelevant and garbage data leads to a huge wastage of money, time and other resources by churning out irrelevant and false intelligence.
Ethical implications of using big data
Big data extensively gathers and reviews customers’ information. Therefore, a company may have several concerns about the impact of regulations related to customer privacy.
How to address the big data challenges?
These issues might seem daunting at first. However, they can easily be dealt with. Here’s what you can do to tackle the above obstacles:
- To get around the budgetary restriction, companies can opt for modular solutions based on their business objectives. For example, enlisting the help of an analytics company to generate a specific report like a Popular Content Report, which is delivered to you periodically based on relevant social media conversations. The insights from this report can boost marketing by establishing the business owner as a thought leader or keeping the sales team updated about the crucial information they need to know. This approach is very cost effective and addresses the business’s priorities. For more information, check out On Demand Analysis service.
- Every company wants high ROI. VOZIQ, through its synergy of platforms, industry frameworks and experts, operationalizes the business intelligence for role-based, action-oriented alerts. This ensures that the insights generated do not sit idle but drive actual business actions from your teams. These insights-driven actions ensure that you can maximize the return on investment from the big data program.
- Several companies, including VOZIQ, offer analytics services which include not only technology but also a team of experts which brings with them proven processes and domain experience. Such a team works as an extension of your internal teams to design and implement a custom big data analysis program. This way, you don’t have to bear the cost of expensive big data technology development and instead get the benefits from the expert solutions of the service provider.Check VOZIQ’s professional analytics services
- The concern over data quality can be addressed through better technology as well as human intervention. For example, VOZIQ employs five advanced analytics engines which are designed to find relevance in the large pool of data. These find the most relevant business insights and KPIs about your customers and competitors. Secondly, the human intervention by VOZIQ analysts (check VOC3 Intervention Service) ensures that the quality of the data as well as the insights is of the highest accuracy and relevance.
- For ethical implications, one must simply remember that big data is ethically neutral as long as a customer is not deceived into sharing his/her personal data. Companies can use this data to offer better customer experience without sharing or selling the data to third parties.
