Thursday Jul 14, 2011

Oracle Fusion Human Capital Management Application uses Oracle Data Mining for Workforce Predictive Analytics

Oracle's new Fusion Human Capital Management (HCM) Application now embeds predictive analytic models automatically generated by Oracle Data Mining to enrich dashboards and manager's portals with predictions about the likelihood that an employee with voluntarily leave the organization and a prediction about the employee's likely future performance. Armed with this new information that is based on historical patterns and relationships found by Oracle Data Mining, enterprises can more proactively manage their valuable employee assets and better compete. The integrated Oracle Fusion HCM Application requires the Oracle Data Mining Option to the Oracle Database. With custom predictive models generated using the customer's own data, Oracle Fusion HCM enables managers to better understand the employees, understand the key factors for each individual and even perform "What if?" analysis to see the likely impact on an employee by adjusting a critical HR factor e.g. bonus, vacation time, amount of travel, etc.

Excerpting from the Oracle Fusion HCM website and collateral: "Every day organizations struggle to answer essential questions about their workforce. How much money are we losing by not having the right talent in place and how is that impacting current projects? What skills will we need in the next 5 years that we don’t have today? How will business be impacted by impending retirements and are we prepared? Fragmented systems and bolt-on analytics are only some of the barriers that HR faces today. The consequences include missed opportunities, lost productivity, attrition, and uncontrolled operational costs. To address these challenges, Oracle Fusion Human Capital Management (HCM)puts information at your fingertips, helps you predict future trends, and enables you to turn insight into action. You will eliminate unnecessary costs, increase workforce productivity and retention, and gain a strategic advantage over your competition. Oracle Fusion HCM has been designed from the ground up so that you can work naturally and intuitively with analytics woven right into the fabric of your business processes."

 

This exceprt from the Solution Brief http://www.oracle.com/us/products/applications/fusion/fusion-hcm-know-your-people-356192.pdf describes the Predictive Analytics features and benefits: "Every day organizations struggle to answer essential questions about their workforce. How much money are we losing by not having the right talent in place and how is that impacting current projects? What skills will we need in the next 5 years that we don’t have today? How will business be impacted by impending retirements and are we prepared? Fragmented systems and bolt-on analytics are only some of the barriers that HR faces today. The consequences include missed opportunities, lost productivity, attrition, and uncontrolled operational costs. To address these challenges, Oracle Fusion Human Capital Management (HCM) puts information at your fingertips, helps you predict future trends, and enables you to turn insight into action. You will eliminate unnecessary costs, increase workforce productivity and retention, and gain a strategic advantage over your competition. Oracle Fusion HCM has been designed from the ground up so that you can work naturally and intuitively with analytics woven right into the fabric of your business processes." ....

"Predictive Analysis Imagine if you could look ahead and be prepared for upcoming workforce trends. Most organizations do not have the analytic capability to do predictive human capital analysis, yet the worker information needed to make educated forecasts already exists today. Aging populations, shifting demographics, rising and falling economies, and multi-generational issues can have a significant impact on workforce decisions – for employees, managers and HR professionals. Not being able to accurately predict how all the moving parts fit together, and where you really have potential problems, can make or break an organization. Oracle Fusion HCM gives you the ability to finally see into the future, analyzing worker performance potential, risk of attrition, and enabling what-if analysis on ways to improve your workforce. Additionally, modeling capabilities provide you with extra power to bring together information from sources unthinkable in the past. For example, imagine understanding which recruiting agencies are providing the highest-quality recruits by comparing first year performance ratings with sources of hire. Being able to see potential problems before they occur and take immediate action will increase morale, save money, and boost your competitive edge. Result: You are able to look ahead and be prepared for upcoming workforce trends."

There is a great demo of Oracle Fusion HCM Workforce Predictive Analytics that highlights the Oracle Data Mining.  This is one of the latest examples of Applications "powered by Oracle Data Mining".

 

Employee grid

When you change your paradigm and move the algorithms to the data rather than the traditional approach of extracting the data and moving it to the algorithms for analysis, it CHANGES EVERYTHING. Keep watching for additional Applications powered by Oracle's in-database advanced analytics.

Monday Jan 18, 2010

Fraud and Anomaly Detection Made Simple

Here is a quick and simple application for fraud and anomaly detection.  To replicate this on your own computer, download and install the Oracle Database 11g Release 1 or 2.  (See http://www.oracle.com/technology/products/bi/odm/odm_education.html for more information).  This small application uses the Automatic Data Preparation (ADP) feature that we added in Oracle Data Mining 11g.  Click here to download the CLAIMS data table.  [Download the .7z file and save it somwhere, unzip to a .csv file and then use SQL Developer data import wizard to import the claims.csv file into a table in the Oracle Database.]


First, we instantiate the ODM settings table to override the defaults.  The default value for Classification data mining function is to use our Naive Bayes algorithm, but since this is a different problem, looking for anomalous records amongst a larger data population, we want to change that to SUPPORT_VECTOR_MACHINES.  Also, as the 1-Class SVM does not rely on a Target field, we have to change that parameter to "null".  See http://download.oracle.com/docs/cd/B28359_01/datamine.111/b28129/anomalies.htm for detailed Documentation on ODM's anomaly detection.

drop table CLAIMS_SET;

exec dbms_data_mining.drop_model('CLAIMSMODEL');

create table CLAIMS_SET (setting_name varchar2(30), setting_value varchar2(4000));

insert into CLAIMS_SET values ('ALGO_NAME','ALGO_SUPPORT_VECTOR_MACHINES');

insert into CLAIMS_SET values ('PREP_AUTO','ON');

commit;


Then, we run the dbms_data_mining.create_model function and let the in-database Oracle Data Mining algorithm run through the data, find patterns and relationships within the CLAIMS data, and infer a CLAIMS data mining model from the data.  

begin

dbms_data_mining.create_model('CLAIMSMODEL', 'CLASSIFICATION',

'CLAIMS', 'POLICYNUMBER', null, 'CLAIMS_SET');

end;

/


After that, we can use the CLAIMS data mining model to "score" all customer auto insurance policies, sort them by our prediction_probability and select the top 5 most unusual claims.  

-- Top 5 most suspicious fraud policy holder claims

select * from

(select POLICYNUMBER, round(prob_fraud*100,2) percent_fraud,

rank() over (order by prob_fraud desc) rnk from

(select POLICYNUMBER, prediction_probability(CLAIMSMODEL, '0' using *) prob_fraud

from CLAIMS

where PASTNUMBEROFCLAIMS in ('2 to 4', 'more than 4')))

where rnk <= 5

order by percent_fraud desc;


Leave these results inside the database and you can create powerful dashboards using Oracle Business Intelligence EE (or any reporting or dashboard tool that can query the Oracle Database) that multiple ODM's probability of the record being anomalous times (x) the dollar amount of the claim, and then use stoplight color coding (red, orange, yellow) to flag only the more suspicious claims.  Very automated, very easy, and all inside the Oracle Database! <script type="text/javascript"> var _gaq = _gaq || []; _gaq.push(['_setAccount', 'UA-46756583-1']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); </script>
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