Many have wondered why one would perform analytics for fraud detection (or prevention) in good times (business as usual) and why would you when there is no whistle blown about a fraud suspicion?
Is this not a grey area where people sensitivities are involved and news about investigations can affect the organization’s brand image? Being trolled over social media that becomes painful to counter? But the CFO’s office is the hardest hit when it comes to answering the Board on the financial losses incurred due to fraudulent activities that leaves a gaping hole in finances.
Traditional anomaly detection is conducted routinely by internal or external auditors. But they are insufficient, not backed by powerful tools and the objective and terms of reference for these audits limit the investigation to a certain level and no more.
Often referred to as “Forensic Audit”, fraud detection methods assume great significance because it requires digging deeper than normal audit to examine and investigate internal control failures, conflict of interest, social networks, multiple factors such as behavioural analysis and ability to crunch big data that can extend / expand beyond the time period under the lens.
A prudent and practical approach would be to set up a mechanism that can proactively provide analytics and flag off high risk areas that need immediate attention.
Fraud Analytics is the use of analytical technology with intelligent business rules and techniques, which will help detect improper transactions like bribery, favouritism, working capital leakage, asset misappropriation, etc. either before or after the transaction is done, so that appropriate steps can be taken to prevent further damage.
Fraud Analytics also helps in performance measurement, evaluate internal control failures and deficiencies, standardize and help in constant improvement that would benefit the overall organization and governance.
Fraud perpetrators use a lot of different and unique techniques which are randomized to prevent discovery and therefore, the techniques used for detection has to be one or many of the following:
a. Capable of running automated business rules that throw up anomalies that can be further investigated for false / true positives.
b. Calculation of various statistical parameters like averages (for example average number of calls made, emails exchanged, delays in bill payments, etc.), quantities (for example comparison of total quantities ordered / received / invoiced / returned), performance metrics (e.g. attrition rate pattern amongst certain departments, sales returns peaking immediately after monthly close, etc.), user profiles (e.g., interested party contracts, sudden lifestyle changes by the user, behavioural patterns noticed) etc.
c. Trend analysis using time series distribution.
d. Clustering and classification that can help find patterns and associations within data sets.
e. Algorithms, models and probability distributions of various business activities.
f. Machine learning and neural networks to automatically identify characteristics of fraud and used later with increasing Big data inputs.
Having a Fraud Prevention program for controlling fraud risks is an important part of Enterprise Risk Management and provides your investors, partners and auditors with more confidence on your demonstrated ability to tackle the same in a sustained manner and not on an ad-hoc basis.
The author is Managing Principal - Cyber security & GRC at Lydian Global Business Services. Our GRC practice is focused on cutting edge technology and solutions such as Fraud Analyzer and rich content for GRC programs. For more blogs visit https://www.mylydian.com/blog .
Lydian’s compelling combination of deep industry expertise, custom developed Products and Solutions, well-articulated vision and its ability to mix and match the right set of innovation, keeping customer in mind, helps organizations to derive the additional value that businesses expect from their investments in Enterprise Technologies and Digital Transformation journey. Visit our website https://www.mylydian.com for more information.
Launched last summer C/4Hana is SAP’s latest attempt to appeal to users of the CRM market leader Salesforce. Despite all the media coverage and information available on-line, clients are now trying to understand if C/4Hana should be considered as part of future upgrade cycles. As companies adapt business models and launch new IT initiatives to satisfy clients' ever increasing expectations, SAP is playing catch up by continuing to acquire solutions to enhance its existing Customer Experience product portfolio.
C/4Hana goes beyond a rebranding
Although some might unfairly say that this is just the newest iteration of a pure rebranding move, with the launch of C4/Hana, SAP has announced a more comprehensive and well-rounded set of cloud-solutions that integrate front-and-back office in a very powerful way.
C/4Hana is a portfolio of products including previous solutions such as Hybris, YaaS and C4C but also enhancing the offering with new applications such as CallidusCloud, Gigya and Coresystems - which were part of latest acquisitions in the Customer Experience area.
When you think about enterprise functions that touch or impact customers (actions, behaviors, data), SAP offers now better front-office solutions to support marketing, sales & customer services with superior consumer data protection.
What’s the difference between Customer Experience (CX) and C/4Hana?
SAP Customer Experience (or SAP CX for short) is the overall capability that empowers organizations to improve corporations’ service lines (Marketing, Sales and Customer Services) that target, acquire and support clients’ relationships. Customer Experience suite is powered by SAP resources and architecture elements that make it easier to integrate customer-facing business processes with SAP S/4HANA and SAP Leonardo, for example.
SAP C/4HANA is a portfolio of five cloud solutions that uses SAP Cloud Platform as the integration hub with SAP S/4HANA and other applications:
Does SAP C/4HANA require SAP S/4HANA?
Although C/4Hana has a built-in business integration with S/4 Hana, it does not require S4 to run. In addition, C/4Hana will also integrate with ECC. However, it can be deployed on its own without an SAP ERP back end.
We would love to hear from you! If you like this short article, have suggestions for future topics or would like to know more about C/4Hana or other SAP products, please drop me a line.
The author is Roberto Kirsten, a Managing Principal at Lydian Global Business Services. Lydian’s compelling combination of deep industry expertise, custom developed Products and Solutions, well-articulated vision and its ability to mix and match the right set of innovation, practical business problem-solving skills understanding customers pain points and designing right solutions keeping customer in mind, help organizations to derive the additional value that businesses expect from their investments in Enterprise Technologies and Digital Transformation journey.
Finance Transformation in 2019
The terms ‘Finance’ and ‘Digital’ Transformation are used interchangeably to describe initiatives to ‘align finance and operational processes’ to drive organizational efficiency.
Finance is the heart of an organization and a Partner to other functions in business. It plays a key role by providing metrics and performance indicators that show the health of different areas of the organization. It is responsible for regulatory and compliance reporting to external parties. Key activities in a typical Finance transformation are:
Rethink the business process?
Transformation projects begin with examining the objectives and steps in a business process. By identifying drivers and triggers of the process in an unbiased manner, a new paradigm for the activity may emerge. This will enable the business process to be executed in an efficient and optimized manner with the reward of greater productivity.
Use Technology to drive change
The convergence of technologies such as Internet of Things (IoT). Artificial Intelligence (AI) and Machine Learning (ML) have enabled a level of data interchange and seamless connectivity that was previously not practical.
Industrial technologies such as ‘Smart factory’ and ‘Smart Manufacturing’ and the use of sensors and robots allow us to transmit signals and data in real-time and can trigger appropriate actions. Automating underlying activities may translate to a faster, more accurate and efficient ‘financial close’.
Incorporate Risk and Change Management
Controls and governance models have to be defined and implemented for the transformation program to be successful. As new technologies are deployed, new risks emerge and different ways of managing and mitigation risk will have to be employed. The change management process involves:
Communication - keep all parties informed of project progress
Training - train employees on using new processes and technologies
Compliance - compliance and governance programs to manage identified risks.
About the author
The author is Mallika Ramamurthy, a Principal with Lydian Global Business Services (www.mylydian.com). Lydian’s compelling combination of deep industry expertise, custom developed Products and Solutions, well-articulated vision and its ability to mix and match the right set of innovation, practical business problem-solving skills understanding customers pain points and designing right solutions keeping customer in mind, help organizations to derive the additional value that businesses expect from their investments in Enterprise Technologies and Digital Transformation journey.
No one ever paid for a Pizza delivery service. It was always free. It is best kept hidden in transaction value. These days every delivery service is a ‘product’. 2 hours, 4 hours, next day, second day, standard delivery for the same stuff are functionally different products. Customers balk when they are expected to pay premium for faster delivery.
In just over a decade the B2C E-Commerce firms in India too have managed to match or exceed International delivery standards as far as last mile logistics go. Both business discipline and enabling platforms. Amazon still leads on the technology investments in this space. Others with varying motivations have their own business models. Some addressing the main pain of shippers (connecting them to freight forwarders), some of customers (not a good business idea, Doorman failed), some of the fleet owners, some of the delivery boys, some of payment collection agencies. Some leverage synergies in existing businesses in this space. Some struggle with Industry specific last mile issues e.g. replenishing gas stations (SAP Secondary Sales/).
Logistics ‘industry’ experts put last mile unit delivery costs to be roughly half of total door to door laid down costs. Which means for low cost products, free delivery simply does not make business sense. The costs depend on several factors like customer density, distance from nearest warehouse/delivery center, route options, city restrictions on certain modes of transport, acceptance time windows, product type, value, volume, weather etc. Some last mile operators also offer collections and returns service and that often means a phenomenal cost to serve. Esp. in newly pampered consumer markets, customers tend to be more demanding and often unreasonable with the level of service they expect! Someone is paying for it.
Expectations in B2B last mile are no different. Retailers of hardware, home furnishings, pharmaceuticals, Auto spares, construction supplies, bars and restaurants now routinely expect similar delivery speed and timeliness. Esp. since some start ups were funded upwards of 100mn$ in early stage. They now employ 25 yo tall, fair, handsome double masters rock stars as directors and pay them upwards of 100lpa to solve some of the most challenging problems in this space. Something that the brick and mortar empires could not. Back then they used terms like secondary and tertiary transportation when whole of the country was their fiefdom and everything was ‘under the control of a 1944 born manager. Every service provider their de-facto slave! No science. No math. No logic. Just shout.
Expectations are bound to rise and there are many finer elements to consider to achieve an ‘Optimal’ last mile delivery. Most importantly making the experience more interactive with end customers. Esp when somethings that can go wrong certainly will.
The author is Loknath Rao, a Business Planning Principal with Lydian Global Business Services (www.mylydian.com). Lydian’s compelling combination of deep industry expertise and Solution vision wrt its ability to mix and match the right set of software design help customers derive the additional value that businesses expect from their investments in Enterprise Technologies.
Toxic organizations have managers who are more interested in reporting other people’s performance. Especially when the organizations do not have a unified role specific, function specific and cross functional KPI’s and critical success factors designed and bench-marked right at the start. To measure their efficiency and productivity in an unbiased way. Against internal targets and also against peers.
Focus on Marginal, Not Absolute.
Nothing in the world is purely linear. Two variables will always have a limiting relationship beyond a point. Be it in a social, cultural, economic or corporate context. Be it finance, supply chain, manufacturing, human resource or even strength of materials. Key performance metrics and success factors must be sustainable and visible to the right stakeholders at all times. Absolute values of metrics often do not necessarily convey much insight. There is a need for developing metrics that convey not only absolute impact but also ‘marginal’ impact of managers decisions. It should prompt periodic revision of key configuration and design of your processes and applications. A company with good operating cash flows can have poor gross margins vis-à-vis their peers and vice versa. But the marginal impact of reduced operating cash flow is what makes sense. Isolated metrics more often than not are not really actionable. There is some root cause somewhere deep down. E.g. Fill rates or returns of a particular SKU can emanate from a badly scheduled production on a particular machine!
Multiple Sources of Truth.
Enterprise systems footprint is complex is most large organizations. Disparate transaction and OLAP applications and integration protocols makes staging and measuring such KPIs hard. Data warehouse is post mortem. Organizations need real time metrics. Thankfully local alerts and notifications exist for managers to take corrective actions. Control towers and Dashboards continue to be siloed. There are multiple ‘sources’ of information. Multiple sources of truth. Your ERP, CRM, SRM, SCM, HCM, PLM and other legacy applications have phenomenal amounts of data generated in real time, incl. information from external sources. You can derive customer service related metrics from your ERP, SCM or CRM or data warehouse systems. Does your organization have a robust solution architecture for reporting and consuming such metrics in real time? A single version of truth?
The Technology is in Place…But
Yes you can ‘report’ on the fly from your ERP systems (e.g. S4 HANA) but as of now far removed from a unified Enterprise Performance Management ‘Cockpit’. It will get there but a pre-configured set of Metrics does not necessarily help all firms and Industries. Not all metrics make sense. Some metrics can be primary and some secondary. Some metrics are cross-functional. A supply chain manager directly impacts working capital needs of the company but can indirectly impact employee productivity. So, does a marketing manager who launches new variants of same products all the time with no concept of life cycle management.
No Analytics without Metrics.
The trouble is most firms aren’t in that stage of maturity to make good their investments in ‘Predictive Analytics’. Not yet. Using massive amounts of data from internal and external sources to build Regression, Time Series and Analytical models in a meaningful way is hard. The software alone can’t help. They must integrate neatly with your transactional systems. Getting the basic Metrics and KPIs right is the first hurdle to cross. It is relatively easy to implement EPM. It has discernible cultural and financial impact. It builds the base for more meaningful Analytical applications. The trends and patterns ultimately must say something about the Metric and KPIs you want to improve. Something that your customers, investors and peers care.
Every organization needs an EPM strategy of their own to organize, automate, and analyse business decisions, methodologies, metrics, processes and systems to encourage and stimulate appropriate behaviour from different stakeholders. Organizations need to translate a unified set of KPIs into plans, monitor execution, and deliver critical insight to improve financial and non-financial performance. Organizations need to build a strong base before venturing into Predictive and Prescriptive Analytical Applications
This is Part 1 of a series of articles on Enterprise Performance Management, exploring Processes, Methodologies, Frameworks & Technology defining metrics, critical success factors, key result indicators and Key Performance Indicators.
The author is Ram Rishi, a Managing Principal – Finance & Analytics, with Lydian Global Business Services Inc.(www.mylydian.com) Lydian’s compelling combination of deep industry expertise, custom developed products and Solution vision and its ability to mix and match the right set of software and design, help customers derive the additional value that businesses expect from their investments in Enterprise Technologies.