Analytics has become an increasingly hot topic in the age of big data. We gather more and more data every day, but we are still trying to make heads or tails of that data. And analytics is not a new topic: Google Analytics has been around since late 2005 and Google certainly was not the first company to float the concept of being able to make more valuable decisions based on data insights. There is a wide range of companies today offering analytics services, from data visualization specialists Tableau to Microsoft with Power BI to Salesforce with its Wave platform.
At PROS, we see analytics as providing huge benefits to our customers from two unique but intertwined dimensions: the quality of the analysis itself and the insights and prescriptive recommendations it offers to the business.
Simply put, pricing analytics uses data to answer key, foundational questions related to pricing and margin such as:
Where is my business experiencing margin loss?
How much will an increase (or decrease) in price impact sales volume?
What are my accounts with the top and bottom margins?
How do market conditions affect my pricing and how do I use that data to optimize it?
What are the steps in the pricing analytics process?
As analytics and predictive sales and pricing analytics software become more ubiquitous in today’s B2B market, it’s important to understand the different steps in the analytics process. If your organization is considering investing in analytics, it is vital to know the capabilities – and limitations – of any analytics tools or processes you are exploring or intend to deploy. Below are the four main analytics steps that take you all the way from raw data to prescriptive business insights.
This step allows the business to produce reports and data visualizations in ways that can help it support day-to-day operations. One such example of descriptive data — using a car analogy — could simply be your speedometer or fuel gauge. These indicators allow the driver to better understand how the car is currently performing – and allow him/her to extrapolate on future needs.
In this step, the business starts to learn what it can predict with this information. This is where many scientific disciplines come into play – from statistics to physics – to better leverage the information at hand. What can we predict from the knowledge that the fuel gauge is low? What is the expected range of the car before needing to refuel?
Now that the business is able to observe behaviors and leverage data to forecast future behaviors, what can it do to proactively adjust and improve the outcome of our work? In the case of the car analogy, such a prescriptive step might be suggesting that the driver re-route in order to include an appropriately timed fuel stop on his trip from origin to destination.
For the final step, let’s use the car analogy one final time. Some automobile GPS systems attempt to offer a degree of automation by re-routing users in real-time, often with limited success. This is probably the ultimate goal of analytics: to automate well-understood decisions and remove the need for human interaction, while instead focusing users on areas that are not well understood and more uncertain. Some systems today already offer some level of automation based on analytics. Most notably, modern commercial jet aircraft include an auto-pilot feature that is designed to automatically adjust to changing conditions. Only when the autopilot is unsure how to respond do the pilots take over and assess the situation.
The PROS Pricing Analytics Approach
Beyond the four levels of analytics described above – descriptive, predictive, prescriptive and automated – there is one crucial additional aspect that we strive to develop at PROS: analytics availability. There are essentially two ways in which analytics can be delivered: inside of an application through visualization or table-like structures, or via BI tools. It is very important to offer both capabilities to customers. This allows them to be presented with some baseline visualizations to get them started, but also enables them to build their own specific analytics capabilities. The latter is necessary because it is next to impossible to offer a “one size fits” all analytics solution to all customers. Even within the same industry, different customers have different ways of looking at the same data and may need to have it presented differently.
Additionally, with PROS you can build custom dashboards for quick access to preferred data sources. With more than 15 different chart types available, the solution suggests ways to view the same data from an alternative perspective, while maintaining selected context. With these visualizations you can:
Easily spot trends, data outliers and uncover hidden costs
Understand what the revenue drivers for the business are and how rebate programs and discounts affect your margins
Take relevant action to prevent revenue and margin leakage and drive improvements
For more info, check out this video: Enabling Excellence Through Analytics.