How Smart Apps Create Value From Big DataBy Guest Author
By Patrick K. Burke
Data science and analytics are shaping how businesses approach customers while helping to separate the signal from the noise. Companies that invest in predictive and prescriptive analytics are more likely to achieve a competitive advantage in their marketplace, and Tim Girgenti, Chief Strategy Officer at PROS, a big data software company, is eager to put companies on the path to better results through analytics. Girgenti took time to speak with CIO Insight on the state of big data analytics, how smart applications can help neutralize competitors and the new business reality that’s influenced by big data initiatives.
CIO Insight: Is this an exciting time to be involved in big data analytics?
Tim Girgenti: Absolutely. Is there any doubt this is the age of big data? It’s great to see the widespread acceptance of data science and analytics as a way to help individuals, teams and entire organizations get better results. We see it everywhere, from sports and leisure, to medicine, high-tech, food and agri-business, manufacturing, health care and many others.
For PROS, that means there’s never been a more exciting time to provide software that puts big data to work. I believe passionately that big data has ushered in a new age of software, an age of “smart” applications that combine the power of automation, analytics and data science into a single, end-to-end solution. Automation alone is now table stakes. And using science outside of applications just slows down the speed of business. Smart applications that provide real-time guidance at the point of action are more relevant now than ever.
CIO Insight: It’s one thing to aggregate data and turn it into a report. It’s another thing to take data and apply it immediately in a business context. Are we there yet in terms of putting to use in real time actionable big data analytics?
Girgenti: We are seeing more companies put their big data to use in real-time through smart applications that use embedded data science to provide users with real-time guidance at the point of action. It’s the nirvana of intelligence plus execution. And it gets great results.
For example, we have a customer in the food distribution business that sells food and equipment to restaurants. When their sales reps create a quote in their sales application, the quote is populated with recommended, science-derived prices that meet the customer’s expectation of value. And it’s populated with recommended additional products that the customer is most likely going to be interested in buying too. With this solution, customers bought on average 400 more items per month, and the vendor’s margins increased more than 260 basis points. It’s a perfect win-win. Customers are happier, and sales reps are selling more. That’s the power of applying big data science and analytics at the point of action.
CIO Insight: Can you quantify the value of a successful big data analytics campaign in consideration to money, time and better use of resources?
Girgenti: We’ve found that the closer you apply predictive and prescriptive data science to your customer interactions, the easier it is to measure the impact. Whether it’s identifying attrition risk, recommending cross-sell and upsell opportunities, prescribing products and prices, or optimizing offers, smart applications can drive measurable improvements in revenue and profits. Gartner estimates that price optimization alone can drive 1-3% increases in revenue and up to 15% in margins. Smart applications for sales can translate to real financial impact.
CIO Insight: Data is produced in so many places, in so many directions. Does having more data to work with make analytics better, or more complicated and subject to too much white noise?
Girgenti: This is the very reason data science is important. With so much data available, the key is knowing what matters and what doesn’t. Data science helps us separate the signal from the noise.
Here are some examples. A car rental company was able to improve their demand forecasts once they identified weather as a key attribute in driving demand. In another case, a food company identified that customers who bought salmon were also more likely to buy cream, so they created bundled offers. In the airline industry, one carrier identified that customers who ordered special meals were unlikely to cancel flights, which enabled them to evaluate their over-booking strategies. In each of these cases, data science helped distinguish the factors that mattered from those that didn’t, resulting in a more predictive and productive outcome.
CIO Insight: Why should companies invest time and money into an analytics platform?
Girgenti: The business value gained from investing in data science and analytics is too great to ignore. Today, descriptive analytics are table stakes and don’t provide the results companies are looking to achieve. By contrast, companies that invest in predictive and prescriptive analytics–powered by data science–are more likely to achieve a competitive advantage and outperform the competition.
In a study by PwC, companies that described themselves as proficient in using demand analytics estimated they outperformed their industry peers in sales growth, margin growth and profit growth by more than two times, and also showed an eight times better total shareholder return on capital. In the study–and at the opposite end of the spectrum–93% of the companies that didn’t invest in and use analytics admitted to lagging their competition.
Competing without smart applications is fast becoming non-optional. This is the new business reality.
CIO Insight: Is data analytics more important when applied within a company or when applied to understand a competitor?
Girgenti: We find that big data analytics and science are valuable wherever applied. While it’s important to understand the forces that affect your business, it’s also vital to understand the customers you’re serving and where your growth comes from. I believe when companies really know their customers, they’re better able to neutralize their competitors.
CIO Insight: It seems just about everything can be measured, charted, graphed and recorded. Is there any concern over this in terms of privacy or simply too much information being made available?
Girgenti: Data privacy has always been an important consideration when it comes to analyzing customers in the spirit of providing a better experience. This is not new. What’s new is the massive increase in volume and accessibility of customer data. I don’t believe that changes the principle that companies should always treat customer data with great care and sensitivity.
CIO Insight: Is data analytics a trend or a game-changer?
Girgenti: It’s a game-changer for sure, but any good game-changer becomes a trend too. The real question is whether or not you’re changing the game or you’re following the trend? It’s the difference between leaders and laggards. Companies that invest in smart applications to help their teams outperform can have a real advantage over those who don’t.
Tim Girgenti is Chief Strategy Officer at PROS, a big data software company.