By Maurie Cashman
Bringing analytics to life is a crucial part of any business decision-making process. The explosion in the amount of data available and the increasing speed with which industries are changing makes analytics critical for organizational success. This flurry of information is one of the reasons business owners fail to plan for their ownership transition.
The problem with analytics is sorting out the critical value drivers that need to be measured. These are the items that make or break your business. The amount of data available through todayâ€™s information systems can become an overwhelming blizzard that obscure the critical things that you must do well to win.
I have been working with a few clients lately to improve the analytics in their businesses. They each have strong businesses with good trends. However, as the businesses get larger, they become more complex to manage. The step-up in scale can be a difficult one to make because the amount of data multiplies as do those attempting to analyze it. They are ending up with an inch of paper to review each month, which no one has time to do or understands how it all interacts. The trick is to continue to boil down the critical factors of the business and shine the spotlight on those items.
For example, analytics could provide a simplified sales management model that can be an effective predictor of sales in any environment by tracking various stages of performance within the sales process. Analytics could also provide insight into customer behavior that can result in bolder market-entry strategies with less risk to the organization. If you are a manufacturing entity, analytics can provide early warning on process breakdowns or confirm better ways to run the manufacturing processes.
Most organizations are reasonably good at rear view mirror analytics. How did we do last month? How many sales did we have? How many sales calls did we make? However, as organizations move from merely describing what happened, to more predictive analytics, more significant business benefits will begin to be realized. Business leaders need to have a clear strategy that articulates key priorities and translates them from insights to outcomes. They need to be able to predict, with accuracy, the outcomes of their processes and have analytics in place that will allow them to quickly measure and adjust processes to meet a rapidly evolving environment. Without this, any analytics initiatives will fail to deliver desired results.
How to Maximize Analytics
A successful analytics framework needs to ensure that data analysis is action-focused and clearly identify the root causes of an issue. To maximize the value of analytics, organizations need to:
Understand the purpose of the analysis. In other words, why are you analyzing this data and what behavior do you hope to modify?
Ensure they have the right expertise and resources in place, understanding who is going to â€œtake the ballâ€ and how much it will cost.
Have a clear business objective and strategies for action based on the analysis.
Practical Steps To Implement:
Understand the central problem. Take time to understand what the real issue is and get it in writing.
Develop a model that explains the value drivers of performance. This will help to determine important information to analyze and sort out distractions.
Capture the relevant data across the organization. The necessary data and knowledge may exist in different areas and would need to be brought together before any analysis can be done.
Apply simple analytical methods. Applying the right method to the right questions is critical to producing valid findings and allowing you to quickly diagnose and be proactive in your management of the business.
Discuss analytical findings with all stakeholders and be sure that they understand the impact of the information in order to impact results. The results need to be specific and relevant. They need to be presented in a way that is consistent with business strategies and values.
By engaging in conversations around the analytics and ensuring business problems are identified correctly, managers can ensure the data analyzed are relevant, forward looking and that measures are taken to manage proactively.