Cloud, Big Data, and Case Management: Transforming Business to a Predictive Enterprise
“A corporation is a living organism; it has to continue to shed its skin. Methods have to change. Focus has to change. Values have to change. The sum total of those changes is transformation.” – Andy Grove
I was recently interviewed by Tom Koulopoulos, President of the Delphi Group, during the Adaptive Case Management Virtual Summit 2012 (or ACM Live) on the major forces that are shaping business today and how case management and complementary technologies can help enterprises manage this change. The replay of this interview and demo is available here. I encourage you to check it out.
There’s little debate that social, mobile, cloud, and big data are changing our lives in ways we haven’t even imagined, and I can cite numerous examples to prove the point. It’s easy, I think, to see the profound ways in which the trends cited above are impacting business, but here let’s pay special attention to the most recent phenomena – big data.
Big Data is different in scale and significance from anything we’ve seen in the past, and exploiting it properly can improve a company’s strategy, execution, decision-making, and can enable predicting future outcomes. Welcome to the Predictive Enterprise.
OK, back to the webinar. Tom and I discussed how we think case management, combined with the power of big data, provides the best path to the predictive enterprise – to guide enterprises to the best action for the business given a particular problem and minimize costly bad decisions. My goal here is to briefly discuss how I think case management technology and Big Data can help in five fundamental ways:
- Drive intelligence into business operations by helping workers easily understand the relationship and impact of their work
- Provide on-demand analytics to gain insight into trends and help improve strategic decision making
- Increase collaboration to accelerate the time to quality decisions
- Establish context for decisions
- Store documents, interactions, and the process used in a particular case in a secure repository to ensure compliance, governance, and knowledge capture
Traditionally, companies have done a lot of number crunching, examined the behaviors of customers, and tried to understand what those behaviors mean. But it’s been more like “driving in the rear view mirror” (to quote Tom Koulopoulos). Predictive enterprise is much more than BI or data analytics – it’s a far more effective forecasting tool than what we’ve had in the past. It means looking at data across previously disconnected sources, finding hidden connections and relationship, and extracting a trend or a pattern. The predictive enterprise evolves from reporting what happened, to focusing on key business drivers, and ultimately to anticipating the future so that it can take well informed actions.
I think the transformative impact of case management and the value of Big Data is best illustrated in examples of what businesses are doing. Take loan processing – risk assessment and loan origination within the case-based applications of many banks is becoming 10x more accurate and the average time to close a loan is being reduced by 30%. Underwriting risk is significantly reduced by going beyond traditional data (e.g., income, employment history, credit scoring, and home appraisal) to the analysis of elements such as home price trending, census data (e.g., population changes), localized job market trends, geographical hazards, historical loan data, and social/professional history of the applicant. Auto insurance typically looks at data received on the application (6 to 12 data points) and a credit check (1 to 8 data points). However, a more accurate assessment could be realized if telematics information from the applicant’s vehicle (100 to 20K data points) and a social graph check (10 to 1,000 data points) are integrated into the case management process. Finally, in healthcare, emergency rooms are traditionally staffed to serve average daily ER load levels. However, hot weather conditions based on historic and real-time weather data, nearby sporting events or concerts, and traffic patterns could be taken into account to dynamically adjust and predict patient load. Any one trend has small impacts on potential load, but combinations of factors together dramatically increase the likely ER load. If a severe traffic incident is reported to the case management system, wait times could be predicted to be beyond acceptable levels and additional medical staff could be automatically paged. Predictive analytics allows the hospital to provide a high quality of service, while at the same time, improving patient care, and ultimately maximizing profitability.
The mantra of EMC is “transform.” From Joe Tucci on down, we believe this is how a company survives and thrives. I’m also seeing a cultural change occurring within businesses and IT where the cycle time with which new technology is adopted is decreasing. Those of us in the technology industry often take it for granted because we see innovation every day our work. But we’re moving at a velocity that is really starting to test our endurance as knowledge workers, individuals, and consumers. One thing that’s clear is enterprises can’t afford to wait or think they can jump in at any time and catch up. Today, there is such a large risk of being disrupted regardless of the business model you adopt and the industry that you’re in. Your enterprise needs a baseline of agility in its structure, innovation cycles, business model, and applications so it can capitalize on change. The other thing that’s clear is that failure has to be expected. Refining and ultimately perfecting the process through continuous improvement is the best way to succeed. Case management technology enables this transformation.
If you thrive on change, you enjoy innovation, and you want to influence the world in ways that make life fundamentally better, there’s no more exciting era to live in than today.Big Data, Cloud comment below, or link to this permanent URL from your own site.