The data-driven version of crystal balls, predictive analytics, can take your business from guessing to acting in a matter of clicks, as long as those are the right clicks. The promise of predictive analytics is that through a fine-tuned statistical model, your business could be ready to take on any challenge. It could know beforehand the necessary volumes of production, client churn rates and even who will be your next colleague. It even promises to detect possible frauds and alert management before this happens. Also, it can optimize marketing through a detailed analysis of the triggers which can cause clients to react positively.
The speed attribute is offered by the fact that predictive analytics can be performed in real-time. Just feed the data stream into the system and let the predictions flow free. The only downside is that although numbers can be rendered automatically, strategic decisions still require experts.
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As one of the sharpest tools in the business analysis kit, predictive analytics, should become more popular for managers. Until now there were important entry barriers, but as technology advances, it will become only a matter of will and understanding of the potential.
Predictive analytics in a nutshell
This is an umbrella term designating different statistical techniques used to make numerical approximations of future outcomes. The data used includes historical records as well as current information, which is sometimes fed to the system directly. Big data and machine learning techniques are used to analyze data due to its classification under the 3Vs (volume, velocity, variety).
Predictive analytics existed a decade ago, but the underlying tools have changed. It is no longer the work of highly-skilled humans, but that of machines. Of course, the human element retains a role in programming the initial algorithm. Humans will still be in charge of some aspects, they will not become obsolete, just that their role will be more focused on calibrating the algorithm by feeding it with the right data.
Types of questions predictive analytics can answer
So, what can predictive analytics do for your business? It is a way to connect the dots and answer fundamental business questions including but not limited to:
- What is the best assortment of products to keep in stock?
- When should we prepare for a peak moment and by what percentage?
- What are the most likely qualifications needed for our next employee?
- When is the best time to schedule maintenance mode?
- What consumer group is most likely to spend a premium price?
These are examples which barely scratch the surface of what predictive analytics can do for your organization, but are relevant enough to provide an incentive to go further.
Is it for small companies?
As these tools become widely spread, the cost will no longer be restrictive. What was previously only within reach of large corporations will become available even to startups. Assessing uncertainty and preparing for it is most useful for those organizations who have fewer resources to bounce back on.
For small companies, this could also be a growth and competitiveness factor. By using predictions to draft their business plan and better prepare for the future, they stand an improved chance of survival in the long run.
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What can predictive analytics offer?
There are countless applications of predictive analytics in all aspects of a business, from the initial feasibility study to exit strategies. Here is a short list of ways this technology could have a positive impact on your business:
Maybe your initial study missed a few client groups which could be a great business opportunity. You can find this out by looking at sales data or even investigating in detail what are the demographics of those visiting your website and tailoring your strategy accordingly. You could add another language or more shipment methods to serve new categories.
Computer models can help explore different scenarios and create a list of possible next steps, including which products are expected to be more successful. This is a number-based prediction, therefore it should benefit from increased marketing budgets.
Target consumers and employees
Allocating marketing budgets efficiently is a daunting task. Predictions can help companies focus their efforts on those groups which are most likely to produce the highest ROI. Such outcomes are the result of looking at consumer behavior and making the right associations and drawing the correct conclusion.
Experts from predictive analytics company InData Labs explains how this is also the base for recommendation engines, such as those used by Amazon and other online retailers. Since cross-selling can ramp up revenue by up to 30%, it makes sense to use it.
Not only are products the target of this method, but so are people. Companies can use it to assess the need for personnel before it arises, eliminating rushed employment which usually results in sub-par results. Also, it can create a profile for a successful candidate by looking both internally to fit the team, and externally on platforms like LinkedIn to identify key metrics for success in the proposed role.
Create smooth processes
Some of the most dangerous pitfalls for a company, especially a young one, are interruptions at any point along the value chain. Imagine if you could know beforehand that a goods shipment would be delayed, you could stock up on merchandise to prevent a shortage. Also, correctly anticipating peak activity helps you serve your clients and win their appreciation. Predictive analysis prevents these hiccups from happening by giving you precise numbers to rely on.
As mentioned in the section about the types of questions predictive analytics can answer, it can indicate the best times to perform preventive maintenance without affecting the usual flow of work. For transportation companies, it can drastically reduce downtime, idle moments and overburden.
Even internal processes can get a real boost from using predictive analytics. It is a new, automatized expression of control processes which make a company efficient. It can help identify the cause of a problem (low stock on insufficient know-how for example), make predictions about the probability of the problem happening again in the future and could even offer solutions to avoid potential issues.
Register today for Innovation Enterprise's Predictive Analytics Innovation Summit in Chicago on October 30–31, 2018, to gain valuable insights from Bosch, Capital One, Groupon, MIT Sloan School of Management and many more.