Although the key to every success in business is in people, we can’t forget the data aspect of it, business models driving it, and forecasting.

Forecasting, in business, is usually related to the certain volume of: sales, influx of calls, or anything that your company is doing, based off of the historical data. Of course, this assumes that you already have a historical data to look into, based off of which you can see what to expect in the upcoming time-frame (may that be: days, weeks, months or years). Simply stated – forecasting can be presented as ‘what to expect’ in the upcoming time.

General Guidelines

The same, or similar, guideline can be applied to SLA (Service Level Agreement) forecasting – based off of the historical data, or success/target levels – you can assume the future success rates, hence renegotiate the potential changes, or adjustments, within the company, or with relevant stakeholders. SLA’s are used to measure your defined targets, may that be with the internal clients (other departments, management, etc.), or external clients (other companies, or individuals, with whom you have contractual obligations). Good, related article worth looking into.

Key Components

One of the key components of data forecasting is exact measuring, and recording of the data that is relevant to your business, since that will help you out in planning of your staffing needs, business volume, and similar. Now, if you have just started your business, naturally, you don’t have any historical data in which you can look into, and create the forecasting based off of that. In that case, a good rule of thumb would be to look into other businesses that are as similar to yours as possible, and to check on the trends, if anything. ‘Trends’ are usually referred to as data points that go in the certain, logical direction, without interruption. Based off of that, you can create your elementary forecasting that can get you going, at the start of the business. 

Here, Machine Learning and Deep Learning algorithms can help tremendously in terms of analyzing the data chunks, looking for the patterns, and potential ‘spikes’ may that be in demand, or anything that your data is related to. This way, instead of having multiple human resources focused just on that, you can leave it to the algorithms, and automation, to help you with that, further eliminating place for human error. Check out this useful article for more information. 

Once certain time passes (and ‘time’, in this case is any relevant, measurable, unit of time that is important for your business – from seconds, to years), within which you can record certain data, and save it for later, to look into, analyze it, and check for the certain patterns that may be of an importance to you.

When you have a certain amount of data accumulated, you can get into the creation of your forecasting document(s):

  • Identify the data that is relevant for your business (phone calls, e-mails, sales volume, staffing, etc.);
  • Decide how will you measure it, and if you have the necessary tools in place (reporting, recordings, etc.);
  • Determine the time-frame that is important for your business (daily, weekly, monthly, quarterly);
  • Start recording the data;
  • Analyze, learn from it, and compare (month-to-month, year-to-year, etc).

Although forecasting can never be, and shouldn’t be, 100% accurate – it will show the certain trends, or how you can prepare for when, for example, you are expecting your sales to go up, so you can staff accordingly (not, over-staff, or under-staff). This will be good for business, and will be good for your employees, so they won’t be overworked, or unsatisfied. 


All of this, in theory, does sound quite simple but please do ensure to delegate this job to the people with strong analytical skills, and patience. Frequently, companies do hire other companies that are driven by data, understand the business models, and know very good how to interpret it. In case you think that you might not be having skilled people in your company, or your business is growing – this option is worth considering. Although it is another investment in your growing business, it may be one of the best ROI’s (Return of Investments).

We do always support that people, in a company, do need to be taken care of first but, at the very same time, we need to take care of business that, eventually will be taking care of those very same people (salaries, dental and health insurance, vacations). Behind every good business lies very good amount of data, and this shouldn’t be neglected.

If you consider yourself not to be someone who is a data-oriented person – delegate this to someone who is. Don’t forget about it. Need for data, good understanding of it will come – sooner or later, and it does provide one of the basis for your business to be successful, and to grow.

As mentioned earlier, and as similar with the time-units – the term ‘data’ is, in reality, business specific – it can be something that is measurable, and is of importance to you, and your company.

Also, on another note, to better understand the need for data, and adequate planning we can look into the individual data forecasting, and that may be as simple as a household budget, and monthly expenses.

If you’re interested, try creating an elementary sheet (may that be based in a cloud service, or locally – on your computer, or a phone), and start inputting the amount of money that is being spent, and on what is being spent over the course of time (usually during one month). This way, you already have three units that you can compare: ‘When?’ – Over the course of month; ‘What?’ – What did we spent our money on and ‘How much?’ – How much did it cost? As the time progresses, you can filter out that table per amounts spent, days, or sort it as per where the money has been spent (utilities, bills, car repair, and so on). Once the year has passed, for example, you can plan your budget better if you need to go on a vacation. You’ll have a pretty good picture how much money you will be able to save, where did you overspend perhaps, or where can you spend more.


Household budget is just one of many data forecasting examples and, most probably, you already are using forecasting on a daily basis, without even thinking about it. Great, if that’s the case, than you already understand the importance, and benefits of it. Of course, when it comes to business needs, it is way more complex, usually, but the basis are there – gathering of the data, and the end results, which will demonstrate what did you spend on, where can you save more money, and where can you invest more.

Same, general, rules do apply when it comes to SLA’s– one of the pillars of every business. Every business is tied to a certain time-frames, and these do relate to certain projects, usually. Just decide what you need to measure, how will you measure it, what will be the time-frame, have something to compare it to – and you’re, pretty much, off for a good start.

Thank you for reading!

Author: Marko Djapic

Read more posts from the author at Rubik’s Code.