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Knowing where to go next is the superpower of savvy companies. Predictive tools guide executives to better decisions. Yet getting these insights has a history of implementation delays, incomplete information leading to incorrect insights, and predictions too old to be useful.

How do you fix this?

Select personal predictive analytical tools, one that is as easy to use as an Excel spreadsheet, letting anyone create meaningful insights that bring confident decisions.

For many, this delivers better outcomes when compared with off-the-shelf solutions.


Here are 4 reasons why Business Executives should choose custom analytics solutions over off-the-shelf solutions:

  1. First, you cannot buy pre-made models that were built with someone else’s data and expect them to work well with your own data.

Machine learning (ML) models are “calibrated” by using the historical data to derive the best approximation possible. Even if it is for the same use case, a model built elsewhere will not perform well (or even worse, it will not perform at all) when you use it. This means that even off-the-shelf solutions that offer any sort of ML models, will require those models to be “recalibrated” using the user’s data.

That is to say, all the tasks, including data sourcing, data preparation, model building, and model validation, will have to be done somehow by the solution vendor as a part of their implementation – and no doubt you are paying for that extra effort by the vendor.

And, even if the vendor calibrates the model when you first implement the solution, who will refresh the model over time? Because models must be recalibrated periodically as data patterns change or they lose their effectiveness.

  1. An off-the-shelf model may not consider the unique data that a user has.

ML models in an off-the-shelf solution were built using a specific set of data that probably came from the vendor’s experience with a few early customers. It is for certain, that the vendor had to use only data elements that it knew would be available to all customers in the target market because if a model is calibrated with 10 data elements, it must have those 10 data elements wherever it is used, or it will not function.

But no two users are exactly alike. Some will have types of data related to the use case that other customers do not. And that extra data could be particularly useful in making a model perform better. The only way a vendor with an off-the-shelf ML model can take advantage of a new customer’s unique data is to go through the model building process, including data sourcing, data prep, model building, and model validation. If the vendor is doing that, you are not getting an off-the-shelf model, just an off-the-shelf approach to a model.

  1. An off-the-shelf solution assumes model results are of a certain form and content, so the user interface (dashboard) given to the user in the off-the-shelf solution is largely fixed and unchangeable.

An off-the-shelf vendor may provide some minor customizations of their user interfaces, but typically you live with the design that they came up with.

  1. An off-the-shelf solution solves only the use case(s) it was built to address. It may be very good at that. But it cannot be used for anything else but those use cases.


What if your team can customize the analytics solution without the concern of timing?

That is why we built NEMESIS, the advanced analytics platform which empowers business decision-makers to build their own analytics solutions faster and more accurately than off-the-shelf solutions.

NEMESIS is built specifically for business users, so you are using tools designed from your perspective.

You have control over the whole model-building process, from data sourcing to model validation. The model can be scheduled to be refreshed based on your requirements.

With NEMESIS, you can include any unique data, making the best-fit solutions. Additionally, you can completely customize how other users see and interact with the model results.

You can use the platform across the organization and for different use cases. This makes the investment much more cost-effective because you are able to solve so many more problems with a single investment.

With NEMESIS advanced analytics platform, analysts can build the ideal tool for your needs that can be deployed across the organization for a fraction of the cost.

Let us have a conversation about how NEMESIS can help you accurately predict your future.