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For example, Budgeting and establishing operating procedures could be core activities here; Staff – which contains a collection of core work activities that support staffing activities within a business area.
High-quality data is indispensable for informed decision-making, operational efficiency, customer satisfaction, regulatory compliance, and innovation. Operational Efficiency Operational efficiency is another critical area where data quality plays a pivotal role.
The very act of diversifying trade patterns itself does not come without any risk, as transport costs are likely to grow, and companies are forced to operate in unfamiliar markets with unfamiliar bureaucracy. Add in currency and creditrisks, and it’s by no means an easy pivot to make.
He explained that his organization was highly functionalized with separate units for sales, trading, investing, portfolio management, credit, risk, and operations; some of which reported to him and some to the corporate center. She and her customers were basically told to get used to the delays.
” For example, if a person was deemed a low creditrisk, granted a loan, and then defaulted on that loan that would be a false positive. The model falsely predicted that the person had low creditrisk. And it needed to operate alongside existing data science workflows so the innovation process is not hindered.
To date, most Big Data accomplishments have involved operational cost savings or allowing the analysis of larger and more diverse sets of data. Yet, these remain largely back-office operations; they don’t change the customer experience or disrupt traditional ways of doing business.
Think of the colleges that are increasingly able to identify students at risk of dropping out and intervene before they do. Or lenders’ enhanced abilities to gauge creditrisk. Energy, agriculture, insurance, retail, human resources — no industry is unaffected. But this shift shouldn’t just be about capabilities.
Ash Gupta is President of Global CreditRisk and Information Management at American Express, and Guy Peri is Chief Data Officer and Vice President of Information Technology at P&G. Both are addressing cognitive applications that benefit customers and bring operational business value to their own organizations.
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