The Data Analytics Conundrum
Studies after study have shown that data analytics is more effective and efficient at detecting risk, and identifying control weaknesses, non-compliance, and inefficient business processes. Chief Executive Officers (CEOs) have repeated stated that data analysis expertise is a much needed skill and software surveys over the past 10-15 years have rated data extraction, data analysis, and analytical and visualization software as critical tools for effective organizations. Why then do more than half of organizations still rate their analytic capability as poor or needing improvement?
First off, I am not talking about Big Data or AI. I mean using analytics to obtain an in-depth understanding of the operational data that currently supports your business processes. All business processes run on data; and, until you understand your operational data, you are missing opportunities to improve and reduce risk. In addition, you won’t be able to use unstructured data, predictive analytics, or AI.
I have been a user and proactive advocate of analytics for close to 30 years. I have been asked hundreds of times, “How can we develop and maintain an analytics capability?” Too often senior management gives up without even trying (“we are doing good work now, why change things?”); or only make a feeble attempt at it (“let’s get a programmer right out of college and have them develop analytics for us.”).
All you need is a plan, and a good understanding of your current state and where you want to be. The plan must address the need for people at the appropriate level and number, technology - data and software - and changes to business processes. It must also have a project manager who will be held accountable for delivery on the plan, clear objectives, milestones, and a reporting requirement – to senior management and the Board.
A statement I hear often is, “We are a small organization, and we can’t afford to dedicate a person to analytics”. It is usually used as a rationale for not using data analytics. My response is something along the lines of “Does being small mean that you can afford to be less efficient and effective?” The reality is, unless you are using analytics, you are not addressing risk, testing controls, examining compliance and improving business operations to the extent that you should be; or you are using more resources to do this than is needed. If you are going to decide not to use data analytics, at least make it an informed decision. Examine the costs and benefits and then decide. It is not a question of doing more with the same resources. Don’t simply look at your existing resources, which are most likely being used to the maximum, and decide that you can’t take on anything else. Ask yourself if there are things that you don’t need to be doing and if they are better ways to do what you need to do. Also look at what you are not doing and determine the value-added if you could do them. Then decide if you can afford not to be using data analytics.
If you decide that analytics are a worthwhile endeavor, the next question is do you have the right resources. Analytics requires an understanding of the business processes, and the data and the IT systems supporting them. These skills will not be provided by junior level business or programming resources. Rarely will all these skills exist within one individual; and they might not currently exist in your organization. Rather than being an impediment, this is an opportunity: an opportunity to obtain the right resources and task them with a clear objective. If you are lucky and have the appropriate type of resources in your organization – this is ideal. Existing resources should already know the business processes and perhaps have some analytical capabilities. However, they will need to be supported by training and software; and given time to develop the skills and implement the analytics functionality. Most importantly, they will need to be dedicated to analytics. Otherwise you end up pulling valuable resources away from other priorities and tasking them with something in addition to what they are already doing; or settle for a subset of the required skills. In either case, it is a recipe for failure.
River AA has the resources, skills and expertise to assist you with these requirements: knowledge of the business processes and the underlying data, and of the analytics that can derive value-added returns. We have developed 1,000’s of analytics that can quickly and easily be configured to run in your SAP environment. These analytics test controls, highlight emerging risks, and identify process inefficiencies and non-compliant practices. They support business owners for accounts payable, purchase cards, travel and entertainment expenses and finance.
RiverAA offers a tiered solution to your analytics conundrum. Tier 1 is the base level and it identifies the business process, data sources and analytics that you want to implement. The standard analytics are then configured to run in your environment. These can be run when and as required. Tier 2 is specifically designed for organizations that don’t want to run the analytics themselves. RiverAA runs and analyzes the results from the analytics and provides business process owners and senior managers with monthly or quarterly reports. These reports highlight the control weaknesses, areas of non-compliance and inefficient operations; and provide recommendations to address them. Tier 3 is the ongoing maintenance and support of installed analytics. This includes modifications to address changes in business processes and the implementation of additional analytics. This ensures that a robust set of analytics are available and continue to provide valuable information. Tier 4 takes to another level: real-time monitoring of transactions with alerts to the appropriate business process owner. This provides business owners with up to the minute dashboards containing critical information on transactions and controls. Tier 5 is the white-glove service wherein RiverAA runs and monitors the real-time analytics; and provides real-time alerts when action is required.
In conclusion, there are many options that will allow you to start and continue using data analysis. You will need to plan and manage your adoption of analytics. It will take time, resources, and technology – internal or external. It has to be integrated in the operational process and developed with an understanding of the business processes and the underlying data and IT systems. It is easy to do wrong, but worth doing right; and we can help you.
Why did I title this “The Data Analytics Conundrum”? Because I don’t understand why organizations are still only talking about data analytics and not simply getting on with the job. Stop asking questions about analytics - get off the fence and actively pursue it. The successful implementation of analytics will add significant value to the organization and support the goals and objectives of senior management.