Data that is incomplete, incorrect, poorly segmented, or miscategorized is a disaster. It foils timely operational action, good customer service, and implementing strategies. A rough estimate is that bad data costs companies as much as 15% to 25% of their revenue. Getting high-quality data, running it through appropriate analytics tools, and applying the resultant insights form the core of the digital transformation across enterprises. And making sense of the raw data needs technology and costs money.
Rahul Chopra of Clix Capital points out that technologies for efficiently leveraging data are getting quite a common day by day largely due to the rise of public clouds, which offer numerous services that can be leveraged for collecting, storing, and converting data into meaningful information. “Earlier one needed to invest huge capex for such data-driven technologies, but now one can try with different options/services in the public cloud and see what suits them best. Moreover, instead of investing in capex, it is shifted to monthly usage cost, which makes it affordable for even small business to consider and invest,” he says.
NOT AN UPWARD TREND
Shreeraj Deshpande of Future Generali India Insurance does not see an increasing trend in the cost in view of advancements in technology and availability of granular data from various touchpoints. “Only ETL, or ‘extract, transform and load’, doesn’t suffice to make the best use of the data for the data preparation process and managing it in different formats. Hence data wrangling (ie. to manage the newly generated data from various sources for analysis) is necessary. Data wrangling is used for improving the analysis process of complex problems during data preparation and tools devised to perform data wrangling are very much available these days,” he explains.
For Rahul Bhargava of InCred, costs, in this case, are either flat or on the verge of falling. Quite a few vendors and service providers, he says, have mushroomed in the past few years, who are providing software as a service, including open source technologies. Such options are being pursued ubiquitously.
“They could take a physical copy of a document with all kinds of data and return them into digital format after deciphering all the elements in it. For instance, based on the data provided, they can detect salaries from a page and check if they are within the salary range and check for address proofs for validating identity, etc,” he adds.
MEASURES TO CUT COSTS
As the cost of storing data is high, says Prashant Deshpande of Shriram Transport, the company has enabled de-duplication with various compression ratios. This reduces the space required for data storage, cooling, and the power cost of the operations. “We have designed a hyper-convergence infrastructure for our storage environment with software designed network in a virtualized environment. This ensures intelligence is built-in for managing technology cost and resources at every level,” he elaborates.
Rachit Chawla of Finway Capital finds the cost trends going downwards because a lot of technology companies have emerged recently, and they are offering great services at the best possible price. They are also working from a standpoint where they want to acquire as many customers as possible, he says, emphasizing that as the technology is already there, the field is highly competitive but the cost is on a downwards trend.
Nilesh Sangoi of Fincare Small Finance Bank too feels technologies for data de-duplication, validation and enrichment have matured significantly and offerings have increased over time. The costs, therefore, are on a downward trend, he adds.
HR COSTS CAN BE HIGH
What about the cost of human resources for acquiring and managing data?
Rachit Chawla does not find any major uptrend or a downtrend in this realm. He says HR resources are actually stagnant at the moment because of the covid pandemic and enterprises are still working at the same cost as they were earlier. “However, managing data is proving to be very expensive, the reason being it is like shooting arrows in the dark as they don’t know which customer will get acquired. It’s all too random and the odds are stacked against you as well,” he avers.
Shreeraj Deshpande says when data is the key for any organization to succeed and remain profitable, educational and training institutions have grabbed the opportunity by offering curricula related to data, so the relative supply of average skilled manpower is there in the market to fulfill the organizations’ needs. “When it comes to resources required not just to maintain the data, but to strategize data storage, consumption and analytically use of this data, the crunch is there and hence the cost is on an upward trend for such highly skilled manpower,” he points out.
Prashant Deshpande says the data storage team at the data center at Shriram Transport gets trained regularly by OEMs and technology partners. And with this training, these data specialists are equipped with the latest skills and techniques to ensure swift, safe and secure operations. “With a full understanding of data privacy and its value, we have tied up with respective OEMs to avail onsite resources and made significant investments in data security. Through hybrid management, we avail both onsite and offsite resources which ensures reliable data management, always,” he says.
SKILLSETS ARE RARE
Rahul Bhargava of InCred does not see any affordable or economical resources or service providers. People who crunch data, he says, are a great resource to keep for businesses, and they are an expensive resource to hire.
“It is an uphill task to seek, recruit, and keep talented individuals motivated to work within a firm. Any data that is used is made valuable only by skilled professionals who can figure the business out, as the data made available to them is enormous. There is a high demand for data scientists and data engineers across the industry, and the trend is expected to continue upward, making it an expensive proposition,” he adds.
Nilesh Sangoi says the data acquisition market has witnessed continuous growth in the past few years and is projected to grow even further, which in turn increases the demand for the skillful resources. He is of the view that while there are a lot of new resources with data engineering skills getting added to the workforce, the demand is outstripping supply, and hence the cost of skilled human resources is going up.