Search Results: api (2285)

Advanced Analytics | Analytics
Mike Gilliland 0
5 steps to setting forecasting performance objectives (Part 2)

And now for the five steps: 1. Ignore industry benchmarks, past performance, arbitrary objectives, and what management "needs" your accuracy to be. Published benchmarks of industry forecasting performance are not relevant. See this prior post The perils of forecasting benchmarks for explanation. Previous forecasting performance may be interesting to know, but

Leo Sadovy 0
Why analytic forecasting?

Because you are already halfway there and you should want the entire process to be data-driven, not just the historical reporting and analysis.  You are making decisions and using data to support those decisions, but you are leaving value on the table if the analytics don't carry through to forecasting.  In the

SAS Colombia 0
Mejore su desempeño a partir del análisis de datos

Es probable alguna vez en su vida haya hecho una matriz identificando debilidades, oportunidades, fortalezas y amenazas (DOFA) en su equipo de trabajo o en su organización y que por eso el tema le suene familiar. Sin embargo, realmente ¿ha hecho un análisis profundo para saber cuáles son sus amenazas?

SAS Colombia 0
Conozca las nuevas tendencias de la gestión del riesgo

Para ganar en el mercado, las organizaciones deben estar innovando todo el tiempo, esto significa moverse rápido, entrar en nuevos mercados estar más accesibles para los clientes, lanzar nuevos productos y tener precios cada vez más competitivos. Pero entre más innoven y compitan, mayores son los riesgos que deben enfrentar

Internet of Things
Anne Belder 0
Why we need digital banks

We often hear from retail bank customers that they aren't satisfied with the revenue captured through digital channels. It was therefore with great interest that I embarked on the mission to understand Chris Skinner’s book Digital Bank. Why we need digital banks The book starts by painting the landscape of

Jim Harris 0
The ethics of algorithmic regulation

In my last three posts on data ethics, I explored a few of the ethical dilemmas in our data-driven world. From examining the ethical practices of free internet service providers to the problem of high-frequency trading, I’ve come to realize the depth and complexity of these issues. Anyone who's aware of these

Work & Life at SAS
Amanda Pack 0
Summer Sweatin': Part I

I love summer. I love the sunny days, the sound of the happy birds in the morning, growing tomatoes in my back yard, and playing outside with my family.  Beach or mountains – I’m 100% beach.  Sunshine or snow?  100% sunshine, palm trees, sand, and the beautiful sound of waves

Analytics
Renee Nocker 0
You snooze, you lose.....

This was probably my favorite of the myth-busters webcasts I have been spewing about, and now I definitely want to meet James Dallas so we can discuss and nod emphatically at each other’s insights on this topic! The “You can’t have analytics without IT” myth is the fourth myth covered

SAS Colombia 0
¿Y si el gol es la estrategia?

La fiebre del mundial por estos días, ha contagiado a millones de personas en el mundo entero. El éxito inesperado de algunas selecciones de fútbol, ha contribuido en gran medida a este aumento de interés, pero también lo han hecho el alto nivel de competencia, la intensa pasión de los

Data Management
Ravi Chari 0
Series: BCBS 239 – Principle 13

Principle 13: Remedial actions and supervisory measures - Supervisors should have and use the appropriate tools and resources to require effective and timely remedial action by a bank to address deficiencies in its risk data aggregation capabilities and risk reporting practices. Supervisors should have the ability to use a range

Data Management
Jose Etchegoyen 0
Series: BCBS 239 – Principle 11

Principle 11: Risk management reports should be distributed to the relevant parties while ensuring confidentiality is maintained. Early in 2013, the Basel Committee on Banking Supervision (BCBS) issued guidelines for banks regarding risk data aggregation and reporting. Known collectively as BCBC 239, these principles were designed to ensure that banks

Jack Hymanson 0
Getting demand in shape

For supply chain managers and analysts Getting Demand in Shape can mean collecting the most pertinent data to support specific business processes and activities. Identifying new or previously unused data sources can be especially important. My most recent article titled “Getting Demand in Shape” in the May / June issue of APICS magazine

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