InetSoft Podcast: Where Predictive Analytics Is Being Used

This is the continuation of the transcript of a podcast hosted by InetSoft on the topic of "How to Apply Predictive Analytics in Business." The speaker is Mark Flaherty, CMO at InetSoft.

Where within the organization do we find predictive analytics being used? Predictive analytics historically has been in two areas. One of the most common uses has been within the marketing organization looking at the likelihood of individuals’ potential purchasing behavior of products and services. What are the influences and impressions of advertising?

We’ve also seen predictive analytics used quite a bit for determining customer behavior. How do we optimize our interactions with our customers knowing that they’re going to react in certain ways based on their demographic profiles or their previous purchasing habits. We’re also seeing now how predictive analytics can be used across the manufacturing supply chain. We’re looking at things like mean time between failure and other particular processes that are well defined. Potential results will be known based on how things are operated.

Besides marketing, customer facing issues and the supply chain, we also do see that many organizations are starting to apply predictive analytics into areas such as sales and finance and also looking at now the potential use of them in regards to working with suppliers and where materials are coming from to actually manufacturer products. Since there’s a lot of information that’s outside of our organization, we can start using predictive analytics as guideposts to everything from potentially prices of how companies stock is trading down to the commodity pricing of materials that are used for manufacturing products as well.

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Maturity Levels of Predictive Analytics

There’s a range of maturity levels in the deployment and use of predictive analytics. We see maturity across multiple levels, and we see organizations who are running at the tactical level, potentially just using spreadsheets and using basic calculations, all the way up to using predictive analytic technology such as SAS where the capabilities can be imbedded within business processes or specialized analytical tools that can be provided to individuals.

As we look at the maturity from organizations who may be more tactical all the way up to innovative organizations, there are many steps in between. We have to step back and look at first the competencies of our people. Do they have the skills and the need for specific kinds of training, the right kind of analytic BI tools? Do they have access to the data that’s required to actually get their job done effectively? Can they actually perform predictive analytics and actually use that information in a coherent way to collaborate with business decision makers and help provide them the information required for understanding when to actually pull back or when to advance their particular efforts.

When you outline a project that you might deploy to improve the availability and utilization of predictive analytics in your organization, what you do is to actually look at your very specific processes. Examples of the ones I mentioned earlier are around customer, marketing, and manufacturing. I would assess where you’re currently applying predictive analytics.

If you’re not at all, the question is why not. And as you look at predictive analytics you’re going to probably need to look at how do you use them with your business analysis. Your analysts across the organization are a strategic asset, and if your business analysts are only doing historical analytics based on what’s happened in the past then they’re not using that knowledge they have on determining the potential future outcomes then we’re probably falling short.

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Infuse Predictive Analytics

So we need to bring an understanding of what they’re doing, where they’re going and how they might be able to infuse predictive analytics as part of their daily and weekly activities to gain better insight then what they may be getting from what went wrong three months ago and exactly what needs to be improved for the next quarter’s performance.

So the two areas that companies are going to have to focus expenditures on are investment in the right business intelligence technology and the training of their people and the processes that are associated with them. They’re going to need to look at their people, processes, and technology to support them to get the information that’s required because the information and how that’s used is at the core of what analytics needs to generate for organizations.

If you’re going to put together an effective business case on this and you certainly are going to have to, one of the ways that we have found most effective is if you can tell executive management and perhaps the board what the implications are of not making this investment, of not spending this money, are.

What is the impact of not having the knowledge of what your customers may or may not purchase from you based on promotions and advertising spend, or what are the implications to our manufacturing processes if we don’t make the incremental investment and improvements to the process and quality of the products.

Of course, quality of products should lead to improved customer service and customer satisfaction. So having very specific examples that today it’s going to continue to require a certain amount of time and certain amount of cost to operate in our current fashion compared to a future state where we can actually invest and imbed predictive analytics as part of our requirement for driving better actions and better decisions, especially in this economic environment, we’ve got to be able to interact and move much more quickly than ever before.

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So in summary, what we got to do is look at how do we make sure that the role of predictive analytics really can deliver the value for business today and make sure that we bring together the multiple components I mentioned; people, process, information and technology to have a homerun for our business.

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