The Ledger

Data & Analytics In The Government

People no longer want to be told what happened the in the past and how; they want real-time information. Even the government is realizing the importance of data and analytics, and how these insights can help deliver the customer promise to their citizens by putting their needs at the core of their decisions. Real-time information and real-time analytics enrich both the government and its citizens with data, which leads to transparency from the perspective of citizens and converts into insights from the government’s point of view. Insights are not only necessary to deliver efficiencies to citizens. To achieve a fiscal balance and internal efficiencies, the governments’ interaction with its extended customer base of employees, suppliers, and partners also needs to be managed and resources optimized.

Read More at The Digitalist by SAP >

The Big Data, Little Brain Phenomenon

Data is now a critical tool for managing most corporate functions and continues to get bigger due to the promise of artificial intelligence, machine learning, and the ease of collecting and storing data. However, managers have been relying on data to guide their decisions without analyzing it properly. Data cannot give insights without being analyzed, and in turn, someone with the expertise to analyze data can’t find insights in just any data. By combining data and the manager’s expertise into a predictive model, finance teams are able to extract the appropriate insights and determine what data is not as important. The increased availability of predictive analytics tools show how crucial there are to an organization’s success.

Read More at The Harvard Business Review >

Quit Searching For Needle In the Haystack Data

When an organization is hunting for insights in their data, they typically don’t have a plan. They have their data scientists spend hours searching aimlessly through unorganized data for any insights they can find. Finding insights this way is extremely difficult, and does not allow the organization to monetize their data. There are three practices these organizations can adapt to drive the value of their analytics, and enables them to monetize their data- decision making, aligning decisions to business objectives, and determining the economic value of these decisions.

Read More at CFO Magazine >

Next Level Analytics Can Lead to Retail Innovation

“New analytic technologies are expected to radically change analytics – and retail – as we know them.”

Retail leaders are focusing on artificial intelligence (AI) tools because they provide better insights to optimize retail execution. AI can be used to automate customer data, upsell options, and pricing engines, to name a few. Retailers are already able to collect large volumes of transaction-based and behavioral data from their customers. As the volumes of data continue to grow, machine learning becomes increasingly essential to further optimize business processes and drive more impactful personalized and contextual consumer experiences and products.

Read More at The Digitalist by SAP >