Chasing Dissonance<\/a> May 1<\/p>\n\n\n <\/a><\/p>\n\n\n\n What does an IR person do?<\/p>\n\n\n\n Read full story<\/a><\/a><\/p>\n\n\n\n Imagine a room. In one corner: management, spinning their narrative. In another: investors, hungry for insight. In the middle, holding a stack of spreadsheets and a red pen, stands the sell-side analyst. Their job? Translate, interrogate, and sometimes, instigate.<\/p>\n\n\n\n Thanks for reading! Subscribe for free to receive new posts and support my work.Subscribe<\/p>\n\n\n\n Sell-side analysts<\/strong>-those folks at investment banks and research shops-are the ones who pick apart public companies and industries, then stitch together reports with price targets, buy\/sell\/hold calls, and financial forecasts. But their real power? It\u2019s in the consensus. Their models feed into the consensus estimates that investors use as the North Star. Miss the consensus, and your stock price might tumble. Beat it, and you\u2019re a hero (for a day, at least).<\/p>\n\n\n\n But consensus isn\u2019t just a number<\/strong>. It\u2019s a living, breathing benchmark that reflects not only management\u2019s guidance, but also the collective wisdom (and folly) of the analyst crowd. When those estimates are dialed in, the market narrative feels grounded. When they\u2019re scattered, uncertainty creeps in-and that\u2019s where risk starts to whisper.<\/p>\n\n\n\n Analysts aren\u2019t just number crunchers. They\u2019re interpreters, relaying management\u2019s story to investors and providing the context that helps everyone make sense of the noise. Their questions on earnings calls, their focus in reports-these are signals, telling IR teams what\u2019s on investors\u2019 minds, what\u2019s misunderstood, and what\u2019s keeping people up at night.<\/p>\n\n\n\n And the relationship? It\u2019s not a one-off transaction. Analysts show up quarter after quarter, at conferences, on roadshows. They\u2019re long-term partners (and sometimes, worthy adversaries) in shaping how the market sees a company.<\/p>\n\n\n\n Here\u2019s where things get interesting. Sell-side estimates are aggregated by platforms like IBES and FactSet, and investors watch them like hawks. Miss by a penny, and you might see your valuation rerated. But what happens when the estimates themselves are all over the place?1<\/a>2<\/a><\/p>\n\n\n\n Academic research tells us that when analyst estimates are dispersed-when there\u2019s no clear consensus-returns tend to be lower. Uncertainty is the enemy of premium multiples. The market doesn\u2019t like not knowing.3<\/a><\/p>\n\n\n\n So, what\u2019s an IR pro to do? First, get curious. Compare the consensus with your internal numbers. Where\u2019s the dissonance? Which line item is out of whack? Drill down: Which analyst is the outlier? What\u2019s driving their model? Did they mention something in their report that explains the deviation, or is it a formula error lurking in a spreadsheet cell?<\/p>\n\n\n\n This is detective work, not just data entry or just monitoring and reporting the numbers to upper management. The goal isn\u2019t to browbeat the analyst, but to understand the narrative their model is telling<\/strong>. Maybe there\u2019s a good reason for the divergence-or maybe it\u2019s just a blank cell throwing off gross margin by 30 percentage points.<\/p>\n\n\n\n At the end of the day, it\u2019s about relationships. The tighter and more accurate the consensus, the more confident the market feels-and the higher the potential for your stock\u2019s valuation. That means staying engaged, keeping the dialogue open, and helping analysts refine their models so the story they tell is as close to reality as possible. This means identifying the root causes for differences in the numbers, it might be one assumption difference in an underlying line item to the main item like revenue or EBITDA that is causing the deviation and reviewing that with the analyst.<\/p>\n\n\n\n Virtua\u2019s solution:<\/strong> Instead of wading through endless tables and charts, you ask a simple question-\u201cWhich analyst is causing the deviation, and why?\u201d-and get a clear answer. Something like:<\/p>\n\n\n\n \u201cAnalyst #9<\/strong> has projected revenue on the lower end compared to consensus. Their gross profit calculation references a blank cell<\/strong>, resulting in an unrealistically low margin. This overstates COGS<\/strong>, which drags down net income versus consensus.\u201c<\/em><\/p>\n\n\n\n That\u2019s not just data; that\u2019s insight. That\u2019s the kind of clarity that lets IR teams focus on what matters: telling a story the market can believe in.<\/strong><\/em><\/p>\n\n\n\n Instead of going through endless screens of BI dashboards, excel and powerpoint files, ask our platform the question you care about and get answers that matter!<\/strong><\/em><\/p>\n\n\n\n 1<\/a> Henry A. Latan\u00e9 and Charles P. Jones (1979) Standardized Unexpected Earnings–1971-77, The Journal of Finance,\u00a0Vol. 34, No. 3 (Jun., 1979)<\/a>, pp. 717-724<\/p>\n\n\n\n![\"Talking](\"https:\/\/substackcdn.com\/image\/fetch\/w_1300,h_650,c_fill,f_auto,q_auto:good,fl_progressive:steep,g_auto\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F291bd037-fb3c-4da0-90de-d21f440a962b_1280x394.png\")
<\/figure>\n<\/div>\n\n\nWhy are sell-side analysts important?<\/h2>\n\n\n\n
The Analyst as Interpreter and Instigator<\/h2>\n\n\n\n
When Consensus Goes Off the Rails<\/h2>\n\n\n\n
The Human Side of Tightening Consensus<\/h2>\n\n\n\n
How we solve this problem using our analytics platform and AI<\/h2>\n\n\n\n
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<\/a><\/figure>\n\n\n\nWhat\u2019s next?<\/h2>\n\n\n\n