Forward-looking analytical tools are necessary for nearly every company, from retail boutiques to the largest technology firms. Reasons for jumping on the big data bandwagon include the need to obtain business data rapidly and efficiently from one unified source, fast company growth or organizational changes such as a merger, or a lack of visibility into a company’s finances. HR and finance departments are taking advantage of the big data trend to discover insights and improve human capital and monetary decision-making.
Prescriptive and predictive analytics are, for many, what they’ve been envisioning when they hear about the benefits of “big data” (which, like the term “cloud” means both everything and nothing, and usually causes more analysis paralysis than anything).
Simply put, big data and analytics technology represents the “great leap” forward from existing data processing software, which allows for analysis that includes third-party or external data along with more flexibility in how to visualize the data. With the introduction of this new software, companies have changed the game completely and raised the bar by moving into prescriptive and predictive analysis.
The Old Way: “What Did We Do?” and “What Could We Do?”
Business analytics have evolved rapidly since the late ‘90s and early ‘00s. Descriptive analytics is what businesses use to answer the question of “What did we do?” Essentially, this is reflective data analysis – a look backward to learn what went right or wrong so that we can try to repeat the good while leaving the bad.
As analytics and computing became more powerful, we shifted toward predictive data analysis, allowing users to look at more data and ask the question, “What could we do?” Predictive data analytics looked at a much greater amount of data that was both internal and external in order to take the information in the past, compare it to different scenarios, and give businesses the ability to make better decisions knowing what would most likely result in the best-case scenario.
The New Way: “What Should We Do?”
With big data, we’re stepping through the looking glass, because we can finally ask the question, “What should we do?” This is a huge leap forward into prescriptive analytics. Simply put, these are intelligent, real-time analyses of historical data coupled with pre-configured sources of data designed to provide users with data-based recommendations addressing specific business scenarios. Leveraging predictive and prescriptive analytics is key for companies to transform their finance and human resources departments. Still with me? Let’s take a look at an example.
Real World Example
Meet Sue. Sue is a business line manager who’s reviewing her team. She notices several members of her team are in very high demand in the market, and unless she takes some corrective action, there’s a 90% chance that one of her top performers – let’s call her Jane – is likely to leave in the next six months. Sue doesn’t want to lose Jane, but she doesn’t know what corrective action she should take. Offer Jane a raise? What if Jane isn’t motivated by money? Maybe a raise will only prolong the inevitable, with Jane leaving in nine months instead of six.
Using advanced predictive and prescriptive analytics, Sue can see that statistically those in Jane’s position tend to remain in the same role for an average of 2.2 years before being promoted. Jane has been in this role for nearly three years. Moreover, when those in this role have been promoted, those who were promoted to a position like Product Manager tend to remain with the company and be more productive.
In this example, big data and analytics technology offered transformational insight into the business. With this information, Sue is able to get ahead of the problem and address the situation proactively, potentially saving herself, her employee, and the company a great deal of time, money, and resources. Rather than offer Jane a raise, Sue now knows how to appropriately advance Jane, recognizing her strengths and offering an opportunity for internal growth and development that Jane would likely have sought elsewhere. And even though Sue will still have a hole in her staff, she can strategically recruit without overloading herself or others in her department and can leverage Jane’s experience by having her train her replacement before moving on. Now Sue is able to make better human capital decisions that help her company achieve HR and finance transformation.
The Science Behind Big Data Applications
Thousands of rows of data in their raw form are nearly useless. However, this data represents untapped potential and with cloud-based technology, companies can analyze it to find insights that lead to better decisions and strategic business endeavors. Big data becomes truly powerful when it’s translated into the language of leadership and new products and services emerge as a result of the analyses.
Certain recently-developed cloud-based big data and analytics platforms are ‘adaptive’ applications that get smarter over time, becoming more intuitive as more data becomes available for particular business scenarios. Unified with an HCM and Financial Management platform, these applications pull and analyze data from across the enterprise in real time. It’s this expansive foundation of real-time, unified data and analytics that gives finance and HCM software its strength and makes it such a valuable tool for organizations.
Simply connecting a Business Intelligence application to HR and Finance applications would, in an ideal situation, provide different tools and applications together. At most, users relying on legacy ERP applications are able to review previous decisions and make predictions based solely on their own historical company data – decisions made in a bubble.
Over time, recommendations become more relevant to each user and each organization, which further reinforces the message that there’s greater value to the organizations when running on a single unified system. This would not be possible if the same enterprise were running a more traditional hosted or on-premise Enterprise Resource Planning platform, such as Oracle or SAP.
To find out how big data and advanced analytics technology can be leveraged to achieve HR and financial transformation at your organization, take a deeper look at our Solutions page.