Les outils de prédiction (« forcasting ») se sont grandement améliorés au cours des vingt dernières années, malgré le fait que les économies soient de plus en plus interdépendantes, complexes et changeantes. Selon KPMG, 13 % des entreprises errent au sujet de leurs prévisions, ce qui constitue un manque à gagner considérable.
Il devient très couteux pour les entreprises de faire des erreurs de prévision. Selon,
*, dans un article paru récemment dans Chief Executive Magazine, les hauts dirigeants et le conseil d’administration sont, en grande partie, responsables de ces erreurs.Heureusement, les progrès spectaculaires attribuables à l’ère numérique peuvent aider les organisations à mieux appréhender les tendances du futur et à améliorer leur compétitivité. L’auteur ne livre pas de recettes miracles mais il donne quelques exemples très éloquents.
Je crois que les CA doivent poser la question qui tue à leurs dirigeants : « Sur quelles bases prévoit-on la pérennité de l’entreprise ? »
« Quels instruments de prévision utilise-t-on ? Et que font nos concurrents à cet égard ? ».
L’article suivant devrait vous sensibiliser à l’importance de bien faire ce travail de prévision.
Voici un court extrait de l’article. Bonne lecture !
Why CEOs Must Change How Their Organizations Forecast
Forecasts are the foundation of all operational and strategic plans. If the forecasted expectations fail to align with reality, CEOs suffer the brunt of their decisions. The business literature is littered with dozens of examples of leading companies forced to concede missed expectations based on a failed forecast. The result is lost revenue growth and shareholder value, if not the CEO’s job.
This problem is acute and getting worse. Companies, on average, are missing their forecasts by an average of 13%, according to a KPMG survey. Altogether, they say, this adds up to more than $200 billion in projected revenue that was forecasted to materialize, but ultimately failed to happen.
Why do so many companies miss their targets? One answer is clear: Their CEOs are basing their decisions on half-baked assumptions, conclusions driven solely by the organization’s internal business data. The potential impact of external events is either generalized or disregarded in the analyses.
In an era of constant macroeconomic and geopolitical upheaval, creating a forecast leveraging just the company’s internal data is like predicting the temperature outside one’s house based on how warm it is inside. Yet, it’s this external information that can often make or break a forecast. No global company, for instance, is immune to the ongoing volatility in Asian markets. None can discount the effects of a weakened Euro, the gyrating cost of energy, or the rapid impact of innovative technologies on consumer behaviors.
Emerging economic trends in a geographic region may influence interest rates, inflation and credit capacity, resulting in higher than projected business expenses. Even changing weather patterns can disrupt supply chains and sharply curtail a country’s GDPt, snapping shut consumers’ wallets, when the forecast predicted rising disposable income.
This wide and growing range of potential outcomes from external events is lost in many of today’s forecasts, as they are focused on last year’s quarterly business data to guide next year’s quarterly projections. Target setting without external analyses is like tossing darts wearing a blindfold. Such dangerous forecasts lower the odds of a CEO making superior decisions on whether to enter or exit a market, develop a new product or stick with the current lineup, or engage a new geographic territory.
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The bottom line: CEOs can no longer rest comfortably, assured that their business forecasts are accurate or even useful to their decision-making. With their jobs increasingly on the line for missing Wall Street estimates, the time has come to invest in robust forecasting tools with predictive data analytics that take into account the world around us.
*Rich Wagner is the founder and CEO of forecasting solutions provider Prevedere. The company’s cloud-based solution collects and analyzes more than 1.5 million global variables in real time to enable companies to systematically compare and correlate internal and external data to predict future revenue and costs.
A reblogué ceci sur capdetformationet a ajouté :
prédiction ou tendance ?