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5 Steps to Improving Sales Forecasting Accuracy

Updated: Aug 23

The sales forecast is the most important number to any organisation. It provides the foundation for all investing and spending decision that will fuel its’ growth. Therefore, the sales forecasting process is a key activity that you cannot do without. It is imperative for businesses to produce predictions based on demand, performance, and trends in order to stay ahead of the curve. What’s more, the fast-paced nature of the tech industry that often brings uncertainty with it means that planning ahead is all the more important.


However, in today’s world, sales forecasting deems to be challenging for many businesses as they fail to forecast accurately - with fewer than 20% of sales organisations having a forecast accuracy of 75% or greater according to Miller Heiman group. The main reason for this is the lack of a well-constructed organisation-wide forecasting strategy. Thankfully, it doesn’t have to be this way, as there are certain things a business can do to stay ahead of the curve and make inaccurate sales forecasting results a thing of the past.


With that in mind, the following article will take a closer look at the source of the issue and suggest how to implement appropriate sales forecasting practices.



Four Barriers to Effective Sales Forecasting


Sales forecasting practices are incredibly useful for businesses in more ways than one. After all, they allow businesses to be better prepared for future events. At the same time, sales forecasting ensures that a company can make well-informed decisions using reliable data, as opposed to relying on information which may be inaccurate. But to achieve the best results, it’s important to adopt the right strategy to avoid common mistakes that many businesses across the world continuously make.


1. Data is incomplete, incorrect or unavailable

One of the most common issues that affects forecasting accuracy is the quality of your data. Most organisations are making decisions based on data that is incomplete, incorrect, and unavailable. Not including data as a key driver in your business strategy is one of the most common mistakes. It affects the type of forecasting data that needs to be collected within the business processes. If this hasn’t been considered – you are already working with a major gap.


Other common issues affecting data quality can include such things as a sales representative either not having sufficient information about set deals, and/or (which is the majority of the time) they fail to enter the information into the CRM. The latter especially is a behavioural issue which is often encountered due to two main reasons. (1) a stigma created around entering data into the CRM as ‘’admin’’. Organisations need to move away from this and incorporate data collection and capturing as part of a sales representatives’ role. (2) Sales people displaying over-confident, conservative, or sandbagging their sales forecasts.

2. Subjective vs. Quantitative methods

Due to the inequality of the data and often for larger organisations the added disjointed (legacy) technologies displaying different numbers for the same question, organisations aren’t able to use quantitative techniques for sales forecasting and resort to using their judgement or ‘’finger in the air’’ decisions.


One of the most notable mistakes is utilising subjective sales forecasting methods, as these are often thought to provide inaccurate results (at least when used on their own). By taking advantage of the quantitative sales forecasting methods, businesses can paint a more accurate picture of what is in store for them in the future.


Luckily, many businesses have become wise to this in recent years, with many realising that subjective sales forecasting can be enhanced by combining it with data-driven and quantitative methods which are renowned for being far superior when it comes to providing predictions for the future.


3. Lack of organisation-wide Forecast Process & Policy

Although sales forecasting is a key business activity that organisations do regularly, no organisation-wide processes and policies have been established. Most organisations tend to use a very independent approach to sales forecasting. Each functional department develops a sales forecast geared towards its specific requirements. The problem with this approach is the lack of functional integration. There is little or no communication at all, along with no coordination nor collaboration in the process.


Due to this, different departments and regions tend to use varying processes and forecasting methods without first aligning them with business-wide needs. Organisations with multiple product lines sold through different routes to market channels in particular need to consider the right methods and a process for ensuring upwards visibility. Although it may be the case that various processes and methods need to be used, this should be an organisation wide decision. Management can then ensure that certain practices, milestones and data entry standards are applied across the organisation. It is then imperative to establish ownership and a governance process.


4. Lack of a Forecasting Accuracy Culture

A study by Mccarthy et al. in 2006 to explore sales forecasting management change over a period of 20 years showed that familiarity with quantitative methods was rising versus subjective methods. However, accuracy was still not improving despite sophisticated tools and techniques being available. The study found that even when data was available and organisations could make use of quantitative techniques alone, this would fail to improve accuracy as there needs to be accountability on an organisational level. Performance and accuracy of sales forecasts will only improve when companies commit to increased investment in more resources and create cross-functional sales forecasting processes - the more people involved in the forecasting process the more accurate; training programs for not only forecasters but also stakeholders subject to forecast to understand the techniques, the process and the systems; finally, a reward system for forecasting accuracy performance.



Best Practices to Break Sales Forecasting Barriers



If your business is encountering all the above barriers to sales forecasting accuracy, it is important to take a step back and re-evaluate your processes and systems. You can take the following steps forward to transform your business.


Review and Organise your Sales Forecasting Needs

Analyse your business. (1) Different functional areas require forecasting at different levels and rhythms. (2) Consider that you may have more than one product line and product items. Organisations with limited product lines can devote considerably greater attention to any one forecast than organisations with a broader product line. (3) What are your distribution channels for these product lines? One product marketed through different channels, with its own demand pattern might have their own forecasting needs. (4) Think of the different go to market regions which will have regional differences and so change the demand and pattern of selling a particular product. (5) Finally, the degree of seasonality of the products you market, affects the techniques used for forecasting. This could also be annual seasonality based on the specific market you are selling to. The Nordic tend to be out for the summer holidays for example – selling to them in this season you could potentially expect lower numbers.


Create a Data strategy around your Sales Forecasting Needs

Assess the historical data such as velocity, conversion, sales cycles, productivity you have available. How old is the data? How detailed is the data? Any other internal and external data you have to create a richer forecast? How accurate is any of the data? What data needs to be collected if there are gaps? In a McKinsey survey less than 50% of organisations actually use all the data available to them that can support with a more accurate forecast. Often is this is because there is a gap in knowledge about the state of the organisations' data. A data strategy is therefore crucial.

Once you can answer those questions decide on the business processes that needs to be in place to be able to collect and capture the movement of the data. Think about the sales processes you have implemented – you need to make sure that these are clearly defined and unambiguous. The transitions between the stages as well as the entry and exit criteria are critical to establish evidence-based milestones. Preferably these are mirroring buyer behaviour rather than internal sales activity.

Finally, consider how you will analyse this data and what quantitative techniques you want to use vs. subjective methods.

Create a Consensus Sales Forecasting Process

In a consensus approach, you create a committee of champions for each functional department as well as a member to be in charge of the committee responsible for creating sales forecasts using the input of each department. This ensures that there are high levels of communication between departments, coordination, and collaboration. The most important part is that there is functional integration to mitigate issues such as bias and political issues. Although this approach is resource and time intensive – when implemented correctly, it can result in superior sales forecasts.

Install the right Forecasting Systems

When looking at systems, you have to make 2 decisions. (1) The best place to capture information in the sales process is your CRM. Ensure you got a robust system in place that can hold your processes and capture the data you need in the sales acquisition process to be able to forecast. (2) Depending on the level of quantitative techniques used, you may choose to do this manually using excel spreadsheet (when a small data set and simple techniques are used). However, you may need a more advanced sales forecasting technology that can integrate with your CRM. Ensure you have considered the best techniques based on your business requirements before acquiring this type of technology.

Build a Sales Forecasting Accuracy Culture

When speaking of accuracy, we are speaking of data. So, when creating a culture this should align with creating a data culture. Organisational culture can accelerate the application of set processes and systems, amplify its power and ensure people on the organisation are doing the right thing. Building a culture usually has to come from top-down. So, all functional department leaders should make this their priority. Revenue leaders specifically are in charge of the number. Their credibility comes from being able to accurately forecast and deliver their number, so accuracy is their number one success metric.


Part of creating set culture is to make every single person in the business accountable for capturing accurate, rich and intelligent information. So, ensure everyone in the organisation is trained on the why, what and how.

One of the most powerful and effective tools an organisation has to drive the right behaviour is compensation. Think of setting up the right reward systems. Build the right sales compensation plan to tie a portion of this to sales forecast accuracy. A known system called the “OFA’ is a compensation system that is based on 3 measures: objective set by the organisation, the forecast given by the sales representative and the actual performance in a given quarter. It gives the sales representative the opportunity to earn bonuses based on their excellent planning capability. A system like this however works well with short-term forecasts.


Moving Forward


So, if you want to make forecasting inaccuracy a thing of the past it is important you re-evaluate your current set-up and build the best foundation and structures. Start with analysing your product lines, distribution channels, your go-to-market and seasonality. Sales forecasting should involve everyone in the business as it needs information on all other functional departments such as marketing, sales and product. Each of these functions require sales forecasts at appropriate levels and rhythm to develop effective plans. Once you understand this, it is important to consider your data strategy and systems to build a stable infrastructure. Sales forecasting is inextricably intertwined with data and systems, so if you want to manage the business effectively you cannot do without. However, the key part to better forecasts is creating a sales forecasting accuracy culture. After all the most important building blocks are the people in your organisation.


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