The other day I was digging around in the extra closet trying to find some shoes that my daughter was needing – IMMEDIATELY. Of course I couldn’t find anything in there, I had to pull stuff out, move things around, etc. until voila, I found the shoes – 2 hours later! Why these shoes were even in the extra closet and not her own closet, I have no idea. My point is that different objects reside in different environments but they still need to be accessed easily.
Sometimes this same type of scenario happens at work, when you are looking for important data that you need. You need to get to information (data) because someone is asking you for it but you just can’t get your fingers on it. There is so much data collected by everyone that it can be hard to put this data to good use, gain insight or analyze what future scenarios could possibly happen.
As we discussed in a previous blog post, a recent survey showed that 87% of businesses expect big data analytics to transform the competitive landscape in their industry over the next three years. But getting to that data, which could be in different environments (closets, if you will) can be a somewhat frustrating task. We can help get to the data so you can use all this data to your advantage.
Analyzing data to make faster, more informed decisions is incredibly powerful. Predictive analytics takes that power to another level. It goes beyond simply reporting on the past. It takes into account many factors, including business growth, cycles, and any other data points that are relevant to giving you a look into the future.
Let’s take a look at how the impact of predictive analytics will be felt throughout the organization.
Marketing Managers: Marketing is obviously excited about new technology. Consumers are generating a wealth of data from mobile devices, computers, communications, and transactions. They are also producing data in social networking feeds. For this data to be valuable, you need systems to respond to it in real time. That takes more than just reports. A recent IBM study found that 90% of marketers feel that personalizing the customer experience is critical to their success. That same study says that 4 out of 5 consumers believe brands don’t know them as individuals.
Predictive analytics can be used to provide additional products that may interest customers based on all of that information. It can use what/if scenarios to determine the right prospects to target. It can calculate the types of customers that have the highest lifetime value and the best ways to extract that value.
Sales Managers: Sales shares a lot with marketing. They go hand-in-hand with generating revenue and profit. Predictive analytics can help the sales team know when to approach existing customers with additional products or services. It can also help them understand new products or services that they should be offering.
Purchasing Managers: They are looking for new ways to analyze price points and contractual options that are being offered by their top providers and combine that with the state of the market. The purchasing manager’s goal is to demonstrate to executives that they are able to comb the market for the best possible deals. They will then use that insight to negotiate favorable terms with existing and new suppliers.
IT Managers: Much like purchasing managers, IT has to evaluate a wide spectrum of options and vendors. They have become skeptical of promises made by those vendors. IT managers want to validate the functionality of a platform and ensure there are no hidden costs. They regularly use white papers, social media, case studies, and peer reviews to make decisions.
Human Resources: HR has lagged behind other departments in their use of data analytics. According to Deloitte, only 14% of HR departments are using analytics. However, this may soon change because HR is drowning in transactional issues. The shift will be for HR to provide advice to management in operations, sales, and finance on hiring decisions and reducing turnover. They can analyze the characteristics of successful employees in a particular role to help hire prospects with similar traits. This can dramatically reduce training costs.
Operations Manager: Among the many needs of Operations, one major need is to forecast inventory. To do this effectively they need to take into account many variables including business cycles, growth, and combine it with outside data such as market performance, related industries, and possibly even weather trends depending on the industry. Many industries today try to predict usage to set pricing (think about airlines or hotels). Automated predictive analytics can provide them with more tools to maximize their profits.
Moving into the Future
Predictive analytics can benefit all areas of the organization. This extends from the office of the CFO to business analysts. Every employee who has to analyze data to make recommendations or decisions can be more productive with a predictive analytics solution.
These are just some of the use cases today for predictive analytics. And we can comfortably predict that there will be more uses that we have not even considered yet. How are you going to benefit from predictive analytics?
Watch this video on analyzing your past & present to shape your future to see how companies are using IBM Analytics – then, give us a shout and we can help you get started!