Enhanced analytics are helping businesses of all sizes unlock enormous potential across their organisations.
Since the days of antiquity, organisations have been capturing data and using it to analyse their performance.
Now, the rise of digital technology is increasing the amount of data you can collect. Unlocking in-depth information which would previously have remained out of reach. This improved technology makes it easier to gather information and extract in-depth details about business operations.
By looking at operations through a data-driven lens, businesses can improve productivity, streamline operations, identify areas of wastage and pinpoint opportunities for improvements. Managers get more information to make key decisions, which helps them steer a more profitable course. By promoting analytics and making it a key part of operations, financial service firms are finding ways to unlock enormous value across those operations.
Financial services use cases
However, what’s lacking in some departments is the understanding of how valuable this data can be. And how to make the most of it. So what are some of the ways IT managers can overcome resistance and inertia to truly harness the power of analytics?
A clue can be found in some of the use cases outlined below.
Analytics can be used to assess the performance of trading or marketing activities, identifying areas of loss and areas of profitability.
A CEO can delve into the guts of their sales activities to see which areas are performing well and which are lagging. This can offer previously unhidden insights. For example, a company might focus all its energy on one product because it’s a big seller. However, closer analysis of their financial performance shows that another product might be more profitable, despite having fewer sales. By devoting more time and energy towards the promotion of this product, they can dramatically increase their own profit margins.
It can be hard to quantify the precise benefits of such operations. Some are tangible and will be there on the surface while others might be harder to define. Streamlining operations could reduce the amount of time staff spend on low-value administrative tasks and enable them to spend more on high value strategic operations. By improving efficiency, they increase revenue by upping the yield of their own staff’s time.
Writing in a report into the value of data-driven analytics, Ron Kasabian, Vice President of Data Center Group and Director of Big Data Solutions showed how analytics projects produced $351million in extra revenue for Intel in 2014. They used an Advanced Analytics Practice to improve the accuracy of tests for new chip designs. Intel also used big data to identify leads for their sales team. Since then they have continued to mine big data and believe it’s resulted in an overall $1bn boost to the company, for which CIO Kim Stevenson won the Forbes CIO innovation award.
Of course, there are many other use cases where analytics can be deployed to great effect. For example, HR teams can harness the data to ensure the value of new employees after promotions. Take a fast-growing early-stage company, for example. They may feel they are spending too much on HR and salaries, because people are being promoted to quickly in order to facilitate growth. What if their employees are not capable of doing the job? What if they aren’t worth the value of their new salary? Using analytics, a company can institute a system where an employee does not receive the salary for their new position until they have fulfilled a transitional period and been awarded ‘good’ ratings. This salary could then be backdated to the moment they started their new position. It helps manage costs and also encourages better performance among newly promoted staff.
The success of such projects illustrates the full extent of benefits businesses should expect to see from analytics. However, many are still slow on the uptake. As with any transformation, innovators encounter resistance at various moments along the process. Staff can often become accustomed to working in a particular way, and will be more unwilling to change. Infrastructure may need to be overhauled which can be expensive and cause disruption.
Deploying analytics can also be a major technical undertaking. A business must gain the capacity to gather the vast quantities of data it needs in order to implement effective analytics. This includes identifying what data it needs to collect to address certain distinct business objectives and requirements.
One of the biggest problems can be finding people with the skills you need. A survey from MIT Sloane Management found that 43% of companies report that a lack of skilled personnel is a challenge. Strangely, though, only one in five had changed their approach to attract talent.
It’s a problem even the largest companies in the world can face. Chevron addressed the challenge of finding well-rounded data scientists by holding a problem-solving competition among its employees. The winner was a woman who had a background in statistics but was working in an unrelated area. She has since grown to become what they call an ‘analytics star’ and they continue to hold the competition every year. In 2015 the Institute for Operations Research and Management named Chevron as the world’s leading organisation for analytics.
“Chevron’s strategy is to differentiate performance through technology,” said Paul Siegele, Chief Technology Officer and President of Chevron’s Energy Technology Company. “Advanced analytics and operations research are critical to helping us stand out from the competition and confer significant advantages.”
In years to come we may look back on this time and think of it as the era when analytics came of age. Data is growing, as is the technology required to capture it. As businesses become more sophisticated in harnessing and analysing their data, they are unlocking vast reserves of potential from within their organisations. The challenge for businesses today is to understand the benefits of analytics and how it can give them a leg up against their competition.