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  • Writer's pictureAhmed Abaza

How Can Predictive Analytics Build Unprecedented Growth & Operational Excellence?

Updated: Jun 9, 2020

Use Cases on how Predictive Analytics can offer growth and dramatic improvement in your business' operations!

Can Predictive analytics get you more revenues, save costs or upheave the performance of your next marketing campaign? Let’s find out!

Can I make you see the Future?

No, I cannot! Though, I can very much tell you what to expect.

To elaborate, let’s say you are in an adventure, wondering the market jungle. You face a cross-road, A & B. While I have never taken either either roads, I can tell you that taking road A, has 90% chance of a safe and happy return, with lots of stories to share with friends and family. Road B has 10% of safe return, with a high chance of meeting an angry grizzly and I am 90% sure of my prediction.

How did I know?

I looked at the trace on the ground, and found that out the 10 shoe traces on the ground, going onto road B, I found only one coming back, that is, besides the foot-print of a big grizzly bear. On the other hand, road A, had out of the 10-foot prints, 9 returning, and no signs of grizzlies. So, if I were you, I’d take road A.

So by analyzing trends in the past, I was able to deduct the probabilities of different events in the future, recommended the best path, aligned with your objective (To be back in one piece in that scenario) and this is how predictive analytics can save your life!

This is of course an oversimplified example of how predictive analytics work.

What is Predictive Analytics?

In short, Predictive Analytics help people & businesses predict future outcomes by processing, manipulating, integrating and mining many types of data, leveraging techniques such as assorted mathematical models, Machine Learning and Probability & Statistical modeling. These techniques are made to build versatile predictions with a high degree of precision.

Why is Predictive Analytics Good for you?

Predictive Analytics is a very powerful tool, to proactively work on risk prevention, cost saving, identifying risks (business risks, not grizzlys) and exploiting business opportunities such as making significantly greater decision making, increase marketing conversions and sales.

With predictive analytics you can transform and up-heave many of the following:

  • Create more accurate business projections

  • Radically improve savings and expenses

  • Get much more out of your marketing investment, in terms of conversions, engagements and ROI.

  • Really tighten up your supply chain and increase its productivity

  • Acquire more customers and give them a stellar experience increasing their engagement

  • Increase employee engagement, make better succession planning and proactively improve your employee turnover

  • Improve delivery times, item shelf lives, inventory turnover..

  • And many many more...   

How it Works?

Very simply put by modeling the data, and finding relationship between data features, and putting them in some sort of a “function”, validating or “Testing” theis function for how well they can predict the data, and you can, with high confidence predict the outcome of future events.

You can use a machine learning algorithm to predict the demand, market price, closing a new customer for example. The machine learning algorithm will take any of from data, and do thousands if not millions of calculations, trying to find valid correlation between the data features, giving a “weight” to each feature, that is, how this feature can impact the outcome of your “target value” (the value you want to predict), put them all in a “function”, and finally brings you the prediction you need.

Let’s say you want to predict the price of a house for example, in a specific area and the house data you have are composed of:

  • Square foot: SQ

  • Age of building: AG

  • Number of Bedrooms: (Beds)

A function of the above can be expressed in the following:

$ Price of the house: = 200 * SQ + 3 * Beds + 50 * AG

Calculating this equation will get you the price of the house.

Machine Learning can calculate vastly more complex functions and equations, with much more features and can output staggering accuracy in predictions.


To make this more tangible, I will give some example of use cases of predictive analytics applications in business.

Use Case 1: Business Development

As Mariam El-Dafrawy requested, here’s an example of a use case for Business Development.

While business development has a vast scope of work, I will try to be as relevant as possible.

If you are working on expanding your business, and starting new branches, in a new location. During the years, you surely have amassed a lot of data about your customers, delivery times or distribution scheduling. You can combine it all, mine it, and build a predictive analysis, of what this new store sales can look like. You can also collect external data (Data that you do not collect in your daily operations), such as Stock Market, Consumer Price Index, Fuel prices, or competitor market spending in that area, and you can increase the certainty of your prediction of your sales.

Then you can decide if the location you are about to expand in, is the right path forward, or what type of inventory and how many of each item to send daily to this branch.

Further, you can segment customers on purchasing behaviors, and other factors, and create more powerful offerings, and marketing campaigns that greatly increase conversion rates, sales and engagement.

Also, if you are a b2b business, based on your data of sales people, closed customers, acquisition budgets..etc, you can predict which customers are more likely to close with which sales person, in which territory, in which season, thus, predicting your revenues, and have more control on your win rates by optimizing your sales force.

Use Case 2: Business Analysis

Abdulrahman Hazem was curious to look into how predictive analytics can be used for business analysis.

Business Analyst usually go around identifying the risks and opportunities for a certain business in a respective market.

For that matter, predictive analytics can, with a very high degree of precision, predict the impact of new policies, new market entrants , market share, business growth and risks, within the business, such as key employees leaving the company, or an upcoming hurdle in sales. Further, it can recommend to upheave the marketing budget or invest in an employee engagement program to retain the best talents.

On another note, Retailers can easily predict inventory requirements before-hand, hence, you can control your inventory level, cycle times, and inventory turnover. Predict the impact of expanding to new locations, and demand on each branch.

Also, if you are a company that works with selling commodities, or volatile pricing markets, you can predict the average market price before hand, with great precision, and be proactive about your daily pricing strategy. Business analysis is an even bigger scope of work, so to give an idea of how it can work, here’s a very nice infograph by ust-global on the areas of a business, by which predictive analytics can upheave:

Picture from UST-global report

These applications of predictive analytics can save millions of dollars, and build an unprecedented competitive advantage for the different businesses.

Use Case 3: Software Decision Making

Based on Hassan El Ghawaby's preference, of course decision making in software is more of the classical applications for Machine Learning and Predictive analytics.

A very relevant example is your facebook feed for example, is personalized to your taste, based on your past behaviors and clicks, by predicting the posts that you like and click through. No wonder social media platforms such as facebook are so addictive.

Personalization in software development is very powerful with predictive analytics. Software developers can build very personalized experience to each user, based on their behavior, demographic, location and many other factors, so they can easily predict from where you will take the next ride, or when you are most likely to click on an email or ad.

Bonus Use Case: Predictive Maintenance

Many manufacturing plants are hindered by unplanned downtimes, or lack of spare-parts. Predictive analytics can prove to be very powerful in that arena, by predicting malfunction and downtimes, so that line and procurement managers can be proactive in ordering the spare part or supplies needed to be used in the next manufacturing cycles.

The power of foresight is long preached in philosophy, Mythology and fantasy. More than ever, businesses are amassing huge amounts of marketing, operations, sales and many other data types, that can be mined and processed, to generate business predictions, that can upheave business performance and build competitive advantage in an unprecedented way.

Many companies are starting to see the unprecedented opportunity, predictive analytics can create for a business, This is why the market for predictive analytics is seeing very rapid growth, as you can see from the figure below.

I am fairly certain, that investing in predictive analytics, will get you a x1000 fold your investment. So, start your data strategy now, and embark on your predictive journey, it can both save you great costs, upheave your revenues and in some cases, prevent deadly grizzly encounters!


Founder & CEO of Synapse Analytics on how AI can be used in Retail. Synapse is a data science and AI company based in Egypt. Synapse Analytics

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