GITNUX MARKETDATA REPORT 2024

Forecasting Statistics: Market Report & Data

Highlights: Forecasting Statistics

  • By 2022, the global demand forecasting software market is expected to reach $1.2bn.
  • 86% of businesses aim to reduce stock-outs with accurate demand forecasting.
  • 45% of businesses with more accurate forecasts have more efficient supply chains.
  • Only 31% of organizations are able to accurately forecast future performance.
  • Companies with accurate sales forecasts are 10% more likely to grow their revenue year-over-year.
  • The weather forecasting systems market is expected to reach $2.3 billion by 2025.
  • 70% of CFOs said they saw improvements in forecast accuracy using forecasting technology.
  • By 2026, the demand planning & forecasting software market is projected to exceed $1.4 billion.
  • 60% of manufacturers indicate that better forecasts could help reduce inventory levels.
  • The energy forecasting market is expected to grow at a CAGR of 4.6% from 2017 to 2022.
  • The total global weather forecasting services market could reach $1.56 billion by 2020.
  • 47% of companies select accuracy as the most important measure of forecasting success.
  • Roughly 80% of businesses use time-series forecasting methods.
  • More than 50% of organizations indicated that improving forecasting accuracy and execution is a top priority.
  • The global business intelligence and analytics market is projected to grow to $22.8 billion by 2020, driven by the need for more accurate forecasting.
  • 59% of companies utilize cloud-based forecast solutions.

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Understanding the future is essential in every entity’s strategic decision-making. This is where forecasting statistics come into focus. Just as a radar scans ahead to anticipate changes in weather, Forecasting Statistics adopts mathematical models and analytical techniques to anticipate future trends based on past and present data. This powerful statistical tool provides businesses, scientists, governments and even individuals with insights and predictions to aid decision-making. In this blog post, we delve deep into the realm of forecasting statistics, exploring its principles, methodologies, applications, and importance in today’s data-driven world.

The Latest Forecasting Statistics Unveiled

By 2022, the global demand forecasting software market is expected to reach $1.2bn.

Peeking into the near future, a significant assertion unfolds; by 2022, observers can anticipate an $1.2bn inflating bubble enveloping the global demand forecasting software market. This projection, featuring prominently in the sphere of forecasting statistics, offers insight into the escalating importance and attractive profitability of this burgeoning sector. As businesses increasingly value data-driven decision making, this statistical tease encapsulates the tremendous potential for growth, revenue, and innovation in demand forecasting software. The realization of this forecast will unquestionably reshape the landscape of business efficiency and strategic planning, highlighting the indispensable role of statistic in defining market trends and potentialities.

86% of businesses aim to reduce stock-outs with accurate demand forecasting.

In the realm of Forecasting Statistics, the figure ‘86% of businesses aim to reduce stock-outs with accurate demand forecasting’ dramatically illustrates the indispensable role that precise anticipation of customer demand plays in the business environment. This noteworthy percentage accentuates how critical it is for businesses to operate without stock-outs, effectively tackling the risk of revenue losses and disappointed customers. Leveraging accurate forecasting not only optimizes the supply chain but also empowers companies to maintain a hold on their market placement amidst stiff competition, affirming the tremendous weight that accurate forecasting carries in contemporary business strategy.

45% of businesses with more accurate forecasts have more efficient supply chains.

Highlighting that 45% of businesses with more accurate forecasts enjoy more efficient supply chains serves as a testament to the transformative power of precise forecasting. Within the sphere of a blog post dedicated to forecasting statistics, this fact underlines how honing the ability to predict future trends or outcomes not only mitigates risks but also enhances operational efficiency, particularly in relation to supply chain management. It implicitly entices businesses to invest in developing robust forecasting models, demonstrating that a nearly half of their counterparts who’ve mastered this art have reaped substantial benefits in form of streamlined supply chains.

Only 31% of organizations are able to accurately forecast future performance.

In the realm of forecasting statistics, the finding that a mere 31% of organizations can accurately predict future performance plays a critical role. It’s a wake-up call, drawing attention to the pitfalls and uncharted terrain in the discipline of forecasting. Highlighting this percentage alerts organizations about their confusion between the predictive mirage and the reality of their forecasting capacities. Moreover, it serves as a rallying cry for improvement – nudging them towards better understanding, refining their statistical models, and making data-backed decisions that could fundamentally improve their forecasting accuracy. Consequently, this statistic is not just a sign of the current times, but a beacon leading the way towards an era of enhanced forecasting.

Companies with accurate sales forecasts are 10% more likely to grow their revenue year-over-year.

When focusing on forecasting statistics, the ability of companies to precisely predict their sales cannot be overemphasized, notably as it links directly to year-over-year revenue growth. With proper sales forecasting, businesses are seen to have an increased chance of expanding their revenue – a likelihood quantifiable by 10%. This intriguing figure illuminates the power of accurate projections in driving financial growth and solidifying a firm’s market standing. Thus, commentating on the vitality of sales forecasts isn’t merely theoretical; it’s a tactical strategy substantiated by a tangible upswing in revenues.

The weather forecasting systems market is expected to reach $2.3 billion by 2025.

A predicted surge in the value of the weather forecasting systems market to a staggering $2.3 billion by 2025 provides compelling evidence of the growing significance and investment in forecasting tools. It underpins the increasing reliance industries and governments worldwide place on weather prediction data for strategic decision-making that reduces risk, enhances productivity, or alerts to natural calamities. Thus, signaling the need for more nuanced, technology-backed statistical analysis in this field, anchoring the crux of our blog post about Forecasting Statistics.

70% of CFOs said they saw improvements in forecast accuracy using forecasting technology.

In the realm of forecasting statistics, the assertion that 70% of CFOs observed advancements in forecast accuracy due to technology illuminates the tangible impact of this digital revolution. This statistic brings to the spotlight the transformative potential of technology-driven strategies in enhancing forecasting accuracy, supplying organizations with reliable data for informed decision-making. Palette of new possibilities offered by technology for keen CFOs redefines the game of business operations by transitioning from conjecture to a science of statistical precision, thereby enhancing forecast accuracy and grounding decisions in hard data over gut feeling.

By 2026, the demand planning & forecasting software market is projected to exceed $1.4 billion.

Sailing through the ever-changing seas of modern business, it’s crystal clear how crucial demand planning and forecasting tools are for aligning resources and strategy. With a forecast that by 2026, the market for these sophisticated navigational aids will surge beyond the $1.4 billion mark, it rings a bell of profound resonance for any forecasting enthusiast. The projection draws attention to the growing reliance businesses may place on data-driven decisions, taking into account both past trends and predictive analytics for decision-making, thus making it a paramount focus point in discussions about Forecasting Statistics.

60% of manufacturers indicate that better forecasts could help reduce inventory levels.

The statistic ‘60% of manufacturers indicate that better forecasts could help reduce inventory levels’ underscores the profundity of forecasting in economic efficiency. It accentuates how effective forecasting can decrease surplus and wastage, minimizing costs for manufacturers. This percentage not only highlights a significant connection between inventory management and forecasting, but also implies an area where further improvement can lead to substantial resource savings. Therefore, it paints a vivid picture of the widespread impact and potential benefits of accurate forecasting in the manufacturing industry, and further in the overall business ecosystem. Essentially, it argues compellingly for the critical role of advanced statistical models in business planning and strategy.

The energy forecasting market is expected to grow at a CAGR of 4.6% from 2017 to 2022.

Peering into the crystal ball of the energy realm, a noteworthy numerical revelation stands out: the energy forecasting market, earmarked for sprinting at a CAGR of 4.6% between 2017 and 2022. In a blog post steeping in forecasting statistics, this prediction underscores the burgeoning potential of this sector. The twinning of a growing concern for sustainable energy with advances in predictive technologies cues a resonant crescendo in energy forecasting applications. Unearthing this statistic fuels an understanding of where the energy market is headed, prompting introspection into current strategies and possibly steering towards pioneering efforts that could reshape the industry landscape.

The total global weather forecasting services market could reach $1.56 billion by 2020.

In the swirling world of forecasting statistics, the projected skyrocketing value of the global weather forecasting services market, potentially reaching a colossal $1.56 billion by 2020, serves as a powerful testament to the growing relevance and impact of this industry. This numerical snapshot not only opens a window towards the demand and dynamism prevalent in this sector, but it also underscores the immense dependency of myriad sectors—such as agriculture, aviation and energy—on accurate weather predictions, therefore attesting to the far-reaching implications of forecast accuracy in driving economic and industrial sustainability. Hence, this data point vividly colorizes the broader tapestry of the blog post on Forecasting Statistics with tangible, real-world economic relevance.

47% of companies select accuracy as the most important measure of forecasting success.

In the realm of Forecasting Statistics, the statistic that “47% of companies select accuracy as the most important measure of forecasting success” is a marker of significant priority that businesses place on the precision of their predictions. It showcases how corporate entities assign a high value to the correctness of their forecasts, possibly as a means to enhance their strategic planning, risk management, and decision-making. This emphasis on accuracy acts as a spotlight on the critical role of accuracy, thereby shaping the way statistical approaches and methodologies are developed and employed in forecasting.

Roughly 80% of businesses use time-series forecasting methods.

Woven into the very fabric of commercial savvy, the statistic that nearly 80% of businesses employ time-series forecasting methods demonstrates the indispensability of such techniques in the modern business landscape. Within a blog post exploring forecasting statistics, this figure underscores the potential potency of effective prediction methodologies. It serves to illuminate the extent to which businesses today are dependent on data-driven foresight, and the significant role the statistical science of forecasting plays in driving decision-making, managing uncertainty, and shaping future strategies within the vast majority of enterprises.

More than 50% of organizations indicated that improving forecasting accuracy and execution is a top priority.

Highlighting that over 50% of organizations consider enhancing forecasting accuracy and execution as a major goal underscores the paramount importance placed on predictive strategies in the business realm. In a forecasting statistics blog post, this fact spotlights how attuned organizations are in harnessing the power of predictability to drive decision-making, manage uncertainties, and optimize performance. A superior forecast helps to streamline operations, anticipate market changes, and maneuver competitive landscapes, ultimately fueling robust strategies in the pursuit of business goals. Thus, this statistic emphasizes the vital role of forecasting in steering the course of an organization towards success.

The global business intelligence and analytics market is projected to grow to $22.8 billion by 2020, driven by the need for more accurate forecasting.

Illuminating the inevitable trajectory predicted for the global business intelligence and analytics market, an impressive upsurge to $22.8 billion by 2020 is expected. This upswing embodies the escalating demand for precision in forecasting, making it a key pillar to be reckoned with in the ever-evolving domain of Forecasting Statistics. The prediction not only enfolds the colossal economic potential nestled within the field of business intelligence and analytics, but also underlines the incessant thirst for more dependable forecasting methods in an ever more uncertain world, enhancing the relevance and urgency of mastering these statistical techniques.

59% of companies utilize cloud-based forecast solutions.

Highlighting an especially intriguing trend, the fact that 59% of companies utilize cloud-based forecast solutions is pivotal in unveiling the growing reliance on modern technology for predictive purposes. Within the broad sphere of forecasting statistics, this datum paints a clear picture of the shift from traditional methods towards more advanced, digital platforms for forecasting. It exhibits effectiveness in improving not just the speed of data collection and analysis, but also the precision and accuracy of these forecasts. This new norm sets a benchmark for companies lagging behind, underlining the importance of technologically focused forecasting methods in maintaining competitiveness in the dynamic corporate world.

Conclusion

Forecasting Statistics offer invaluable insights that can guide future decision-making across various sectors. It serves as a road-map, highlighting potential trends and subtle shifts in data that could indicate larger changes on the horizon. Although forecasting is not foolproof and 100% accurate, it allows for proactive planning and strategic adjustments to minimize risks and maximize opportunities. Embracing forecasting statistics, therefore, is essential for personal, business, and government growth planning and should be viewed as a necessary tool in a world increasingly driven by big data and predictive analytics.

References

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FAQs

What is Forecasting?

Forecasting is a statistical technique used to predict future outcomes based on historical data and trends. It provides an estimate of future events and trends in a process, helping businesses to make informed and strategic decisions.

What are the main types of forecasting?

Forecasting methods can generally be split into two main categories qualitative and quantitative. Qualitative forecasting requires subjective judgment and is often used when historical data is not available. Quantitative forecasting, on the other hand, uses mathematical models and historical data to predict future events.

What are some common techniques for forecasting?

Some common techniques for forecasting include moving averages, exponential smoothing, trend projection, and regression analysis. More complex techniques, such as machine learning and deep learning models, are also being increasingly used.

What factors can influence the accuracy of a forecast?

Many factors can influence the accuracy of a forecast. These include the quality and relevance of the historical data used, the appropriateness of the forecasting method applied, unexpected events (like economic changes, natural disasters), and how far into the future one is trying to forecast.

How important is forecasting in business decisions?

Forecasting is a critical aspect of business decision-making. It can guide a company's strategic planning, budgeting, and goal setting processes. A well-established forecasting system can help a business anticipate future events, prepare for potential risks, and take advantage of opportunities.

How we write our statistic reports:

We have not conducted any studies ourselves. Our article provides a summary of all the statistics and studies available at the time of writing. We are solely presenting a summary, not expressing our own opinion. We have collected all statistics within our internal database. In some cases, we use Artificial Intelligence for formulating the statistics. The articles are updated regularly.

See our Editorial Process.

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