Discover what's news at LatentView Analytics

The company has been looking to diversify into Europe and other markets to reduce its over dependence on the US market

Chennai-based LatentView Analytics Ltd is expecting India and Asia Pacific region to contribute 10 per cent of its total revenue in the next 2-3 years, according to company CEO Rajan Sethuraman.

Currently, the US market contributes over 95 per cent of the company’s revenue followed by Europe (3.5 per cent) and the rest of the world (1.4 per cent). The company has been looking to diversify into Europe and other markets to reduce its over dependence on the US market.

Sethuraman said the company added five new clients during the latest quarter, which includes the company’s first client in India. “We are pursuing 4-5 bigger opportunities in India and expect some of these to get closed in Q4.”

Sethuraman said the company has a healthy pipeline of prospective clients and added that the average deal size of opportunities is much larger than it was earlier. “In the past, we were doing $5,00,000-7,00,000 opportunities but at this point in time, we have at least five opportunities that are larger than $2million.”

He, however, added that large deal prospects also mean complex evaluation processes involving request for proposal (RFPs) and intense competition from other bidders etc.

Sethuraman said while the demand for data analytics remains strong, he acknowledged that deal conversion is taking longer time to fructify as companies are taking longer time due to prevailing macroeconomic uncertainty.

Meanwhile, the company reported a five per cent year-on-year growth in its third quarter net profit at ₹52.5 crore as against ₹49.9 crore in the corresponding quarter of the previous year. The company’s consolidated revenue, yoy, grew by 35 per cent to ₹145.3 crore (₹107.8 crore).

Rajan Venkatesan, CFO, LatentView Analytics, said, Q3 continues to remain a seasonally strong quarter for the company. He said the company’s cash and investments (excluding proceeds from the IPO) as of December 31, stood at ₹773 crore. “Most of this, we will look to deploy into inorganic growth (acquisitions) that we are currently evaluating.”

LatentView Analytics stocks closed at ₹376.50 apiece on NSE, 1.75 per cent lower than the previous day close.

Source: BusinessLine

Net profit of Latent View Analytics rose 5.09% to Rs 52.47 crore in the quarter ended December 2022 as against Rs 49.93 crore. Watch this segment for more details.

Source: TimesNow

The LatentView Republic Day Quiz is back with its 21st edition. The popular general knowledge quiz is back again and is open to participants of all ages. The quiz is for teams of up to three members each. No prior registration is required and there is no participation fee. The event is scheduled at 9.30 am on January 26, Thursday in Music Academy Mini Hall (Kasturi Srinivasan Hall), 168 TTK Road, Chennai.

Data and analytics is clearly emerging as a core activity for enterprises to stay relevant and stay ahead of competition, Venkatesan said.

After making a stellar IPO listing in November 2021 with listing gains of 169%, the Latent View Analytics stock is now trading lower than its listing price of Rs 530, closing at Rs 370.70 on the BSE on Monday. Rajan Venkatesan, chief financial officer, Latent View Analytics, talks about the data analytics market, growth strategy and focus markets in an interview with Ayushman Baruah. Edited excerpts:

How mature is the Indian market in terms of adoption of data and analytics?

Recent studies in the Indian market reveal that almost all enterprises have realised the importance of data science. All organisations are leveraging analytics at some level to improve their decision-making and automate/operationalise processes for better productivity and cost-effectiveness. Banking and retail seem to be at the forefront of adoption. However, studies also suggest that in terms of maturity of analytics function, Indian enterprises are still significantly behind developed countries. This is poised for change as data and analytics become mainstream and data availability, planning and storage get better, and become a part of CXO’s remit to use data to drive decision-making.

What is your growth strategy, including hiring plans, for FY24?

Going into FY24, we feel confident about the growth opportunities and the market potential. Data and analytics is clearly emerging as a core activity for enterprises to stay relevant and stay ahead of competition. We have set ambitious targets for growth and our hiring plans will be commensurate with the growth plans. We will look to hire between 400 and 500 through a combination of campus, off-campus and lateral hiring in FY24 which will translate to about 40% increase over our current headcount levels.

What about your plans for inorganic growth? Which type of companies will you be interested in?

We are actively looking at inorganic opportunities and evaluating companies that will add capabilities across supply chain, data engineering on the capabilities side, serving Fortune 500 clients in retail, consumer and financial services, and having exposure to European markets. Ticket size would be companies between $5-25 million in revenues.

Are you planning to focus on markets outside of the US and which ones?

Europe will be a big focus in FY24 and we will also take small calculated bets in the APAC region, including Singapore, West Asia and India.

Do you see a cut in spend in data and analytics in view of an economic downturn and Covid fears?

We continue to closely watch trends on the ground and work closely with our key clients and stakeholders. While there could be some short-term sluggishness in new initiatives, the medium- to long-term outlook is still positive and on an upward trajectory. We also have the experience of working through a few economic cycles and we believe we are making the right investments in both capability-building and domain expertise that will help us add value for our clients. We have not heard of any substantial cut-backs within our client set. We also believe in an uncertain environment, enterprises will look to optimise spends and will leverage data and analytics even more.

Which sectors are expected to drive growth in the next few quarters?

For us, consumer, retail and financial services will continue to drive growth. ESG (environmental, social and governance) initiatives are also picking up pace and enterprises will leverage data and analytics to drive compliance and reporting.

Source: Financial Express

Imagine that the traditional way of forecasting customer demand is like a train running down a track. For years, it had a smooth uninterrupted journey and then—boom—the train suddenly collided with COVID and derailed. Demand patterns dramatically changed, as did the ability to accurately predict future sales.

For some, the collision caused the train to leave the tracks. We all witnessed companies scramble to keep pace with shifting supply chains and consumer behavior. Many became overstocked with inventory after demand had waned, leading to steep discounts to move stagnant products. As an analytics leader who works with consumer companies, I also saw the opposite, with examples of staggering dips in on-shelf availability and missed sales exceeding 10% of overall revenue.

Getting blindsided by variables such as a global pandemic or economic recession is largely out of our control, but human error or negligence can also cause a train to derail. To avoid this and to get (and keep) accurate demand forecasting back on track, companies need to completely rethink the status quo.


Historically, demand forecasting involved looking at and extrapolating past sales data. This approach has utility, but the COVID collision suddenly changed what consumers purchased—as well as when and how—making past sales data far less reliable than ever. A CRI report found that “69% of retailers and 66% of consumer products companies had difficulties in demand planning due to lack of accurate and up-to-date information on fluctuating customer demand.”

Additionally, demand forecasting involves a great deal of human hypotheses. Demand planning and marketing teams have highly specialized skills, but they have natural human biases. Human-centered forecasting is constrained by the limits of human knowledge. Subject matter expertise is crucial, but it only accounts for a few of the drivers that impact demand.

Purely human-based demand forecasting is also subject to the tendency of people to try to game the system. The tactic of overinflating in order to stay ahead of demand may seem like a good idea, but can backfire. An example cited in Harvard Business Review is of an automotive manufacturer that routinely inflated its orders to a particular supplier by 10% to 15%. In response, its supplier decided to fill only about 90% of the orders.

So, we must look to data. Reliance on historical sales data and basic time series methods to forecast demand fails spectacularly, however, when demand patterns fluctuate significantly. This is also true for product categories that are erratic or intermittent, or when entirely new products are introduced that have no sales history. So, how can organizations adjust and get back on track?


Examining data from a variety of sources (both historic and real time) and understanding how those different pieces fit together provides a more well-rounded view of what organizations might expect in the future. Organizations need to use and corroborate data across multiple channels (online, offline, mobile, curbside, etc.) to understand true demand by category.

External data, earned data, and paid data sources are all crucial. Companies can use internal data to carefully select sales history data that accounts for pre-pandemic, pandemic, and “new normal” behaviors. Online shipping data can provide better insights for demand patterns.

Along with sales data, considering the impact of marketing and promotions can provide deep insights, particularly if that data is broken down into above-the-line, below-the-line, and digital campaign information. Social media, SEO, and search trends may also be correlated to consumer behavior and provide valuable information in demand forecasting.

With all these different sources of data, it’s possible (and increasingly helpful) to employ machine learning technology to better predict future demands. Predictive models allow for real-time adjustments, so that a flawed demand forecast can be corrected with minimal financial impact. According to an analysis by McKinsey: “Applying AI-driven forecasting to supply chain management, for example, can reduce errors by between 20 and 50 percent—and translate into a reduction in lost sales and product unavailability of up to 65 percent.”


Consumer behavior and preferences continue to change rapidly, and macroeconomic conditions remain uncertain. This makes demand forecasting challenging whether you are a legacy big-box retailer or a digitally native D2C brand. This year’s holiday season will serve as a testing ground for many companies as they adjust from last year’s missteps, but the challenges around demand forecasting apply well past any single shopping season.

By leveraging all available data to make real-time decisions, organizations can prevent future derailments. This will require more advanced use of data analytics and the adoption of more flexible demand models to account for outliers and unexpected disruptions in demand patterns. It will also require more creative logistical strategies such as converting underutilized store space into e-commerce fulfillment centers.

One thing remains certain in our uncertain world: Companies must move past relying on past sales data and have a connected view of all their available data to increase the accuracy of their sales predictions and minimize the negative impact of unexpected surprises down the track.

Source: Fast Company


Sitting between what appears to be the tail end of a pandemic and the nose end of a recession, 2023 looks to be what the sports world would call a “rebuilding year” when it comes to tech infrastructure. Business complexity is increasing, the data explosion continues to intensify, tech layoffs have ramped up even as we still contend with a talent shortage and skills gap, and cyberattackers are outpacing cyberdefenders.

Happy new year, indeed.

In the face of these trends, what can IT decision makers expect? We reached out to some of TechBeacon’s contributors from the past year to get their takes on what the new year will bring to the world of IT. Here’s what they had to say:

Vendors will face increased pressure to adopt stronger security practices . . .

“In 2023, from a security standpoint, there will be a redefining of what is means to be a trusted partner. Organizations will need to continue to scrutinize the security posture of their vendors, suppliers, and partners that work as part of their supply chain. Not all partners are alike in implementing security strategies, frameworks, and audit controls. Companies will need to prove that they have implemented the latest technologies—and security-risk assessments and controls—augmented with continuous security audits to ensure that the data sharing and/or exchange are protected, continuously monitored, and tested. Moving into the new year, we will see more organizations adopting risk-management processes, verifying partners with user authentication and authorization and role-based controls, and ensuring that partners have conducted continuous network- and systems-vulnerability assessments, patch management, and penetration testing.”
—Ihab Shraim, CTO, CSC Digital Brand Services

. . . partly because companies will be cash-strapped for direct cybersecurity spend.

“With the world recovering from the pandemic and going through economic uncertainties, businesses are prioritizing cost efficiencies and resource optimizations. That is leading to reduction of budgets for cybersecurity. Organizations are findings ways to automate processes with artificial intelligence (AI) and machine learning (ML), addressing skill scarcity and risk reduction while lowering the costs.”
—Satyavathi Divadari, chief cyber security architect, CyberRes (a Micro Focus line of business)

Cloud evolution will take a back seat to cloud cost-optimization.

“In 2022, we saw that many enterprises were not getting the return on value that many thought that cloud computing would bring. Much of this was because of self-inflicted issues around rushing too fast into the cloud during the pandemic and skipping critical steps, such as application refactoring to leverage cloud-native features and be more cost-efficient. The result is grossly under-optimized cloud-computing solutions that are not able to deliver on the expected ROI. This includes the ability to provide scaling on-demand and business agility as promised and cloud costs that are in many instances twice what businesses expected. In 2023, it will be about building and rebuilding cloud-based systems for cost efficiency. This means leveraging better cloud operations (CloudOps) and tooling, deploying financial operations (FinOps) programs, and reevaluating anything that moved [into] the cloud for potential optimization and modernization. This means that many enterprises will stand still in their evolution to public-cloud providers while spending as much or more on cloud-computing services and technology to retroactively fix avoidable issues.”
—David Linthicum, chief cloud strategy officer, Deloitte Consulting

Tight budgets will also compel software democratization.

“This year is going to be a time for businesses to declutter and streamline their operations. With the economic slowdown and funding crunch, it’s more important than ever they make sure they’re using the right technology to support their business goals. Enterprises should look for solutions that offer more customization and value for the money and reconsider some of the large, inflexible systems that have high maintenance costs. At the same time, businesses will start to see a greater shift toward democratizing technology, with tools that can be used by professionals and all users.”
—Suresh Sambandam, CEO, Kissflow

Meanwhile, data democratization will hit senior management.

“Data is no longer a bastion of IT teams, solely owned and controlled by data scientists and analysts. As the status quo evolves, business leaders will become more data-literate, and, likewise, people deep in the ‘data trenches’ will better understand how and why data must be presented to make decisions. Technology that breaks down silos and unifies the entire data value chain from engineering to insights will underpin this critical meeting of the minds.”
—Tarunya Suresh, head of marketing and demand generation, LatentView Analytics

Exploding data growth will drive tech firms toward AI/ML innovation.

“IDC has predicted that this year we will generate 118 zettabytes across the consumer and commercial sectors. Yet that data comes in so many forms across so many media that it remains a challenge to throw a net over it all and to understand it. Using AI/ML and related innovations, tech providers will continue to evolve their offerings to handle the challenges of data variance, location, diversity, capture, security, understanding, analysis, and management. The smartest enterprises will need to find innovative and scalable ways to surf the zettabyte tsunami.”
—Derek Britton, director of communications and brand strategy, Micro Focus

AI/ML innovation will make data management a priority.

“The imperative for enterprises this year is getting their data and data infrastructure ready for the AI age. The current buzz around new generative AI technologies such as OpenAI’s ChatGPT is the future; these innovations will change forever the way we create content, solve problems, make decisions, and collaborate in the future. ML models require massive amounts of data to produce accurate, relevant results in these new tools—but this data is often hidden in application and storage silos or lacking the context needed to push it to the right platforms at the right time. The year 2023 will see an insatiable demand to organize, search, tag and intelligently manage the massive volumes of unstructured data volumes collected at the edge, stored in multiple clouds and on-premises data centers. Organizations that can do this in a way that is also sustainable and cost-effective will gain a measurable competitive advantage.”
—Krishna Subramanian, COO, president, and co-founder, Komprise

The Los Angeles Dodgers will win the World Series.

This has nothing to do with enterprise IT. I’m just bullish on J.D. Martinez and Max Muncy.
—Joe Stanganelli, assistant managing editor, TechBeacon

Source: TechBeacon


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