Latest news with #dataanalytics
Yahoo
a day ago
- Business
- Yahoo
Morningstar's CEO Kunal Kapoor on Private Assets and ‘Extracting Gold'
Morningstar's CEO Kunal Kapoor has come a long way since he started at the company as a data analyst in 1997, when he compiled data on mutual funds — sometimes with the help of a fax machine. Today, the Chicago-based firm has become one of the premier data providers on the planet and even offers indexed products, technology and robo-advice for retirement savers. 'My job was basically entering data,' he said. 'Believe it or not, at that time, it was like extracting gold.' The problem was a lack of transparency around mutual funds, where even compiling information from public documents, like yields and total net assets from fund companies, was a challenge. 'Today, we sort of take it for granted, which is awesome.' READ ALSO: Succession Planning Vacuum Risks Alienating RIA Clients, Next-Gen Leaders and Family Offices Explore Private Credit as Private Equity Returns Stall Over the past eight years at the helm, Kapoor has helped the company expand its workforce to over 10,000 employees and boost its stock price more than threefold. Next up is tackling the private marketplace and creating a 'common language' for advisors and investors to research both public and private investments using the same yardstick. 'The private equity and private credit industry is not ready for that level of transparency, even as they have an interest in reaching investors' he said. 'Ultimately, they are going to come around to the view that they have to make it simpler.' Kapoor chatted with Advisor Upside during Morningstar's Investment Conference held annually in Chicago. What's your take on the massive public-private market convergence? The public markets will remain the mainstay for most investors. [Private markets] have to adopt a framework that'll allow for easier transactions and for lower costs. Do I think what exists today for advisors is best in class? No. Do I think that because advisors are starting to get more heavily involved in the space, it's going to lead to better products, and lower-cost products, and more transparency? Yes. It's a journey, as with all things. What shouldn't be lost is that there's a really important reason why it's happening: The number of companies that are private has increased. The amount of debt being issued in private markets — outside of the money center banks — is increasing, and so as an investor, you have some clear ability to think about that in terms of how you're building exposure to your portfolio. The truth is more Americans than ever work for companies that are backed by PE. And so, they're partly more familiar, and want to invest in these companies, because they're part of that ecosystem. It used to be that not everybody would get equity and get to participate in its success, but that model has been changing. How should advisors be thinking about deploying these funds in client portfolios? Let's think about it in the context of your 401(k) or mine. Those are elongated assets that are unlikely to get touched for an extended period. So I would say that you could have a higher exposure in that type of vehicle. That's what all the non-profits and universities and endowments do as well, right? Those are long-dated assets. For shorter-term liquidity needs, let's say our emergency six-month fund, it shouldn't have any assets because you should not have any volatile assets in those. So it's thinking about that scale. The other thing I would just point out is this is new and the lack of liquidity is something that investors have to take into consideration. For investors or advisors who've never been in this space, I do think that inching into it is really important, versus kind of plunging. You really need to understand how your clients are going to react to having something that does not have immediate liquidity available to them. What's one issue that's not getting enough attention? One thing that doesn't get talked about enough is that returns have been incredibly strong for the past two to three decades — and that's led to easier conversations with clients. It's also led to easier prospecting and it's largely led to growth in assets. Our data would suggest, and our forecast suggests, that market returns in most asset classes will moderate in the years ahead. I think that is a real challenge, and it's partly because the belief has been out there for a while, but the reality is, the markets have continued to fight the odds. So it's easy to take it with a grain of salt, I guess. But it's always good to be thoughtful around: What if returns are not what they were, how would you as an advisor run your business, manage your clients and prospect for new clients in that type of environment? We've just had such a big run, but the long and short of it is, if you believe in long-term market averages, the US has been above those averages for so long. And there have been many reasons for that, including a period of extended low interest rates. Growth and profits in some companies have hit extraordinary levels, and I think there's just a question about whether they will kind of normalize to historical levels. It's our belief that they will. This post first appeared on The Daily Upside. To receive financial advisor news, market insights, and practice management essentials, subscribe to our free Advisor Upside newsletter. Sign in to access your portfolio
Entrepreneur
a day ago
- Business
- Entrepreneur
Here's Why You Shouldn't Obsess Over Metrics
Opinions expressed by Entrepreneur contributors are their own. Here's a fun thing that happens in product management. You wake up one morning and your daily active users are down 15%. Your conversion rate, though? Up 8%. Customer satisfaction scores just hit an all-time high, but your churn rate is creeping upward. Your metrics dashboard looks like a Jackson Pollock painting, except instead of paint splatters, it's conflicting signals that make you question everything you thought you knew about your product. The thing about metrics is that they're like teenagers. Sometimes they're telling you something important. Sometimes they're just being dramatic. The trick is figuring out which is which before you make a decision you'll regret. Let's start with a fundamental truth: Not all metrics deserve equal attention at all times. This sounds obvious until you're in a meeting where someone is freaking out because time-on-page dropped by 12 seconds. Is that bad? Maybe. Or maybe you just made your product more efficient. According to research from McKinsey, companies that excel at data-driven decision making are 23 times more likely to acquire customers. Great. But here's what they don't tell you: Being data-driven doesn't mean reacting to every data point like it's a fire alarm. If you were driving a car and every warning light demanded immediate action, you'd never get anywhere. Some lights matter more than others. Some can wait. The same principle applies to product metrics. Yet somehow, we've created a culture where every metric fluctuation triggers a crisis meeting. Related: 5 Steps to Creating Metrics That Matter for Your Company Decision framework So, when should you actually panic? Here's a framework that's served me well. First, look for metric combinations that tell a story. Single metrics lie. When daily active users drop but session duration increases, that's not necessarily bad. Maybe you're shedding casual users while your core audience becomes more engaged. That could actually be progress. The real warning signs come in clusters. Declining user growth plus increasing churn plus dropping engagement? Now you've got a pattern worth investigating. It's like medical symptoms. A headache alone might mean nothing. A headache with fever and sensitivity to light? Time to see a doctor. PayPal discovered this the hard way in its early days. They were obsessing over user acquisition metrics while missing the bigger picture: Their fraud rates were climbing faster than their legitimate transaction volume. The metrics were all there, but nobody was looking at them together. Second, distinguish between leading and lagging indicators. Some metrics predict the future. Others just confirm what already happened. Confusing the two is like using your rearview mirror to navigate forward. Customer support ticket volume? That's often a leading indicator. When it spikes, something is broken. Revenue? Usually lagging. By the time revenue drops, the problem started months ago. Netflix figured this out when it noticed password sharing complaints increasing before subscriber growth stalled. The complaints were the canary in the coal mine. The growth stall was just the inevitable result. Third, understand your metric's natural volatility. Some metrics are drama queens by nature. They fluctuate wildly as part of their normal behavior. Others are steady until something's genuinely wrong. Ecommerce conversion rates can swing 30% day to day based on traffic sources, time of month and even weather patterns. A single day's dip means nothing. But if your enterprise software's monthly recurring revenue suddenly drops? That's not normal volatility. That's a customer jumping ship. Spotify learned this when it initially panicked over daily listening hour variations. Turns out, people just listen to less music on Tuesdays. Once they understood the natural patterns, they could spot actual anomalies. Fourth, consider the cost of being wrong. What happens if you ignore this metric and you're wrong? What happens if you panic and you're wrong? Sometimes the cost of overreacting exceeds the cost of waiting. Imagine redesigning your entire onboarding flow because new user activation dropped for a week. You spend months on the project, only to discover the drop was seasonal. Other times, waiting is catastrophic. When security breach indicators spike, you don't wait for statistical significance. You act immediately because the downside of being wrong is minimal compared to the downside of being right but slow. Related: Use the Metrics That Really Matter in Your Business Metric hierarchy Here's my advice. Build yourself a metric hierarchy. At the top, put the three to five numbers that genuinely predict your business's health. These get daily attention. Everything else? Check weekly or monthly. More importantly, train your team to think in stories, not statistics. When someone comes to you with a metric panic, ask them to tell you the user story behind the number. What's actually happening to real people using your product? The truth is, most metric movements are noise. The signal is rare, which is precisely why it's so valuable when you find it. The best product managers I know have developed an almost intuitive sense for which metrics deserve attention. Until you develop that intuition, remember this: Your metrics are tools, not masters. They should inform your decisions, not make them for you. Sometimes, the wisest decision is to close the dashboard and talk to an actual user. Because at the end of the day, products succeed when they solve real problems for real people. No metric, no matter how sophisticated, changes that fundamental truth. Related: Why Focusing on KPIs Too Much Can Backfire
Globe and Mail
a day ago
- Business
- Globe and Mail
Tempus AI's Data Business Keeps Scaling Up: Can the Growth Pace Last?
Tempus AI TEM, a Chicago-based company focused on precision medicine, is building network effects via its three interconnected product lines. In the first quarter of 2025, revenues in its Data and Services segment increased 43.2% year over year to $61.9 million, driven by a 58% growth in Insights, the company's data licensing business. Gross profit outpaced revenue growth, up 65.2% with only a modest 3% increase in the cost of revenues. The business has scaled significantly, securing deals with companies like Novartis, Merck EMD, Takeda and United Therapeutics over the past year. Against that backdrop, Tempus' ability to sustain such strong growth rates in Data and Services is particularly impressive. Most of these contracts span multiple years, with total remaining contract value reflecting data and services yet to be delivered. Several recent developments are setting the stage for the momentum to continue. A major highlight is Tempus AI's $200 million data and modeling license agreement with AstraZeneca AZN and Pathos to build the world's largest foundation model, bringing AZN's total remaining contract value to over $1 billion as of April 30. AZN and Pathos are also covering a large portion of the compute costs to train the model. Notably, the agreement's non-exclusive nature allows Tempus to license data and build models with others in the future. The company also expanded its collaboration with Illumina, which will use its multimodal data platform to accelerate clinical benefits of molecular profiling across all major diseases. In May, Tempus inked a large data agreement with Boehringer Ingelheim focused on biomarker development and novel discovery efforts, building on their past collaboration. Further, the company's new oncology-focused platform, Loop, is already in use by a large pharmaceutical company to prioritize drug targets in patient subpopulations with severe unmet needs. TEM's Key Competitors in Data and Services ICON ICLR, an Ireland-based contract research organization, experienced a significant increase in overall biotech opportunities and a modest uptick in project win rates in the first quarter of 2025. However, it was ultimately offset by an increased number of customer-cancelled request for proposal (RFP) opportunities. In large pharma, RFP opportunities were softer in the quarter; still, ICLR's high success rate underscored its strong positioning as a strategic partner. IQVIA 's IQV Technology & Analytics Solutions business continued the strong recovery trend in the first quarter of 2025, with clients launching new drugs and executing their commercial roadmaps. However, IQV faced slower decision-making from clinical customers on new programs, reflecting broader macroeconomic pressure and industry caution. IQVIA reported a 10% increase in average time from RFP issuance to award in the quarter, both year over year and sequentially. TEM Outperforms Peers, Industry, But Valuation Stretched Year to date, Tempus AI shares have surged 102.5%, outperforming the industry's 18% growth and also delivering stronger returns than IQV and ICLR. Image Source: Zacks Investment Research TEM currently trades at a forward 12-month Price-to-Sales (P/S) of 8.47X compared to the industry average of 5.83X. Image Source: Zacks Investment Research TEM Stock Estimate Trend As you can see, earnings estimates for Tempus AI in 2025 and 2026 are showing a mixed picture. TEM stock currently carries a Zacks Rank #4 (Sell). You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here. Zacks' Research Chief Picks Stock Most Likely to "At Least Double" Our experts have revealed their Top 5 recommendations with money-doubling potential – and Director of Research Sheraz Mian believes one is superior to the others. Of course, all our picks aren't winners but this one could far surpass earlier recommendations like Hims & Hers Health, which shot up +209%. See Our Top Stock to Double (Plus 4 Runners Up) >> Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report AstraZeneca PLC (AZN): Free Stock Analysis Report ICON PLC (ICLR): Free Stock Analysis Report IQVIA Holdings Inc. (IQV): Free Stock Analysis Report Tempus AI, Inc. (TEM): Free Stock Analysis Report This article originally published on Zacks Investment Research (
Globe and Mail
a day ago
- Business
- Globe and Mail
Palantir Stock (PLTR) Glows after AI Nuclear Power Deal
Shares in software company Palantir Technologies (PLTR) were higher today as it sealed a deal to use AI to build nuclear reactors. Confident Investing Starts Here: Nuclear AI Palantir said it was teaming up with Kentucky-based Nuclear Company to co-develop and deploy the nuclear operating system (NOS). It will be the first AI-driven, real-time software system built exclusively for nuclear construction. It is understood that Nuclear Company will pay the data analytics company around $100 million over five years to develop the platform. Palantir said that NOS will transform the construction of nuclear reactors into a data-driven, predictable process, enabling the Nuclear Company to build plants faster and safer at lower cost. This will include sensors placed across construction sites to feed data in real-time to a digital twin model of the site, and a supply chain system tracking and verifying all parts to save costs, and AI agents reading regulatory documents much more quickly. Record Power This is important because even though the International Energy Agency has declared that nuclear is set to generate a record level of electricity in 2025, construction is being held back by costs, project overruns, and financing challenges. Demand is increasing as nuclear energy is considered to be a cleaner source of fuel and more reliable than wind or solar energy. More and more tech firms are also looking at nuclear energy to help power the growth in data centers and AI demand. President Trump is also supportive, with executive orders, signed in May, directing the nation's independent nuclear regulatory commission to cut down on regulations and fast-track new licenses for reactors and power plants. Is PLTR a Good Stock to Buy Now? On TipRanks, PLTR has a Hold consensus based on 3 Buy, 10 Hold and 4 Sell ratings. Its highest price target is $155. PLTR stock's consensus price target is $104.27 implying a 27.03% downside. See more PLTR analyst ratings Disclaimer & Disclosure Report an Issue
Yahoo
a day ago
- Business
- Yahoo
Verisk Analytics, Inc. (VRSK): A Bull Case Theory
We came across a bullish thesis on Verisk Analytics, Inc. on Monopolistic Investor's Substack by Antoni Nabzdyk. In this article, we will summarize the bulls' thesis on VRSK. Verisk Analytics, Inc.'s share was trading at $309.93 as of June 24th. VRSK's trailing and forward P/E ratios were 45.65 and 44.64, respectively, according to Yahoo Finance. A data analyst using cutting-edge analytics to accurately interpret complex sets of data. Verisk (VRSK) operates as a specialized data analytics provider for the U.S. Property & Casualty insurance industry, offering essential tools to evaluate risk, streamline underwriting, and manage claims. Its platform allows insurers to quickly develop and launch products without spending excessive resources on data analysis, relying instead on Verisk's proprietary models built from billions of insurance records. The company benefits from deep regulatory expertise, long-standing industry integration, and a reputation as the go-to partner for top insurers. While Verisk operates with one reporting segment, its revenue is bifurcated into underwriting and claims services. The underwriting segment focuses on risk assessment and customer eligibility, while the claims segment supports fraud detection, claims processing, and cost evaluation. With minimal cyclicality due to recurring annual contracts and growing subscription-based pricing, Verisk is steadily shifting its revenue model toward committed, predictable cash flows. Financial efficiency metrics place Verisk well above peers, reinforcing its operational superiority. It maintains a healthy balance sheet with positive equity and a strong asset base, although the presence of a modest yellow flag suggests caution. Verisk's dominant position stems from its network effects, unmatched industry experience, high margins, and compliance-enabling products like standardized legal forms. Despite capturing 12% market share, it effectively behaves like a monopoly due to high switching costs and regulatory complexity. However, a discounted cash flow analysis suggests Verisk may be overvalued at current prices (~$298), with fair value estimates ranging between ~$137 and ~$286. While its fundamentals remain strong, limited upside and valuation concerns suggest a wait-and-watch approach for value-conscious investors. Previously, we covered a on Public Storage (PSA) by Antoni Nabzdyk in December 2024, which highlighted the company's dominant self-storage network, operational efficiency, and strong dividend profile. The company's stock price has depreciated by approximately 0.83% since our coverage. This is because the thesis has yet to play out amid broader REIT headwinds. The thesis still stands as PSA's fundamentals remain solid. Antoni Nabzdyk shares a similar thesis on Verisk, but emphasizes its monopoly-like data moat and pricing power in insurance analytics. Verisk Analytics, Inc. is not on our list of the 30 Most Popular Stocks Among Hedge Funds. As per our database, 45 hedge fund portfolios held VRSK at the end of the first quarter, which was 40 in the previous quarter. While we acknowledge the risk and potential of VRSK as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and have limited downside risk. If you are looking for an extremely cheap AI stock that is also a major beneficiary of Trump tariffs and onshoring, see our free report on the best short-term AI stock. READ NEXT: 8 Best Wide Moat Stocks to Buy Now and 30 Most Important AI Stocks According to BlackRock. Disclosure: None.
