A Shift in Technology Thinking
A Shift in Technology Thinking
As a management consultant and leader of ScottMadden’s Corporate & Shared Services finance and accounting practice, I have lately heard quite a shift in CFO thinking toward Business Intelligence (BI) technology solutions. The recession certainly seemed to take its toll on aggressive technology decision-making in the market place. We heard statements like, “if it’s not delivered by our existing ERP system, we won’t even begin to consider it.” Then came the revolution of cloud-based technology. Formerly expensive niche solutions became “rentable” over night. Third party vendors sprang into action producing unique financial solutions that were better, cheaper, and more flexible than many big ERP systems could dare to compete with.
Missed Opportunity Right Under Our Nose?
We now see more CFOs that are concerned they will be “out-innovated” by competitors hungry to harness the power of predictive data analytics. Thereis a growing following that believes the secret recipe to clobbering the competition is out there. But it’s in a raging sea of data that is owned and guarded by their sales, marketing, R&D, supply chain, HR and, yes, even their own finance departments. There’s no such thing as a “Chief Data Officer” in most corporations, and governance around this seemingly infinite set of data, at best, ranges from unstructured to non-existent.
But, “what will I say when my competitor beats me to the punch using some low cost data analytics tool with information that was always right under my nose?” To illustrate, wouldn’t most people say that the country with the largest allocation of budget to their military is clearly the United States? But when this data is correlated to GDP and visualized, the United States is actually a very distant sixth preceded not by Russia and China, but rather by smaller countries like Saudi Arabia and Israel. So, how many arguments and financial decisions do CFOs make based on historical perceptions of truth versus often over-looked but logical facts?
Complexity Made Simple
Steve Jobs once said that making things simple is very complex. Enter, the cloud-based BI technology providers that can literally be installed in hours versus months. Capability to drag and drop data sets over one another, to draw statistically correlations that may enlighten the user with different views and perspectives. And more importantly the ability to visualize the data to emphasize the true impact of relationships or true differences and boil it all down to business language. The complexity is left to the technology providers versus the end users. But, in case you are interested, visualize a large field that needs to be plowed. You could invest in one giant, expensive plow to handle the job.
Or, would it make more sense to carve the field into small plots and invest in hundreds of smaller less expensive plows? The job could be handled in the same time and with the same cost, or less. Now imagine the field growing rapidly, in different directions, or discovering entirely new fields. The small inexpensive solution now presents its advantages in flexibility and scale. Well, consider the same concept with BI tools that are harvesting immense sets of data from your corporate data warehouse and cultivating them into data “cubes,” or even unstructured data from external open sources such as social media or government economic websites. Does your ERP offer expandable, flexible, and user-friendly BI capability? The beauty of new niche cloud-based BI tools is that you are renting versus buying. If another brand of better and faster “plows” presents itself three years from now, it’s not impossible to rent a new system.
What Does BI Mean to Finance?
So, what does this mean to the CFO office? It means there are now lower risk investments in technology that may facilitate the eternal search for a competitive edge, or that keeps your company from falling prey to a competitor that uses business analytics better than you. Of course, this concept expands broader than the CFOs office, but how many sub-optimal financial decisions must we make based on incorrect perceptions? It’s not just about the technology. It’s also about the skill sets that need to be cultivated to use the technology. “Data hounds” often need to be pointed toward their objective to keep them from becoming lost in the woods. The next time you make an important decision based on data, write it down. Once you have a list of four to five of these decisions, challenge an employee in your organization that has good data analytics skills to review the information you used with the assistance of a BI tool. Tell them to cut the data in different slices, correlate it with different sets of information, model predictive forecasts to challenge long-term reliability.
Actually, if they are the right skill set, you won’t have to tell them! You will likely discover new and different insights that may have led to different strategic decisions, or even to different daily operational decisions.
• How much cash should you keep in reserve on a daily basis?
• What is the optimal level of debt for your company’s five-year strategy?
• Are you missing opportunities with foreign interest rates?
• What discount can you ask from vendors for early payments?
• Is my collection team focusing on the right customers?
So How Do I Start?
There is now more reason and less risk to re-consider your technology investment in BI tools. Remember the tool is worthless without a few employees that know how to use it, and a specific question to use it for. A world-class BI model is not developed overnight. Layout a reasonable plan beginning with a tool and just a few analytical skill sets.
Based on your objectives, determine how fast and how far you plan to mature. Measure that maturity on a scale such as the one below and make sure someone is accountable in your organization. If you are struggling getting out of the gates or understanding the concept, use this example as a starter: Data suggest for every $1 Billion of spend, you should be getting $3 Million in vendor discounts. Test this hypothesis in your own company using analytics. On what purchases? With what vendors? At what time in the year?
In what markets? You may quickly find it’s not so easy to gain access to other department’s data and must build a governance mechanism that benefits everyone. You may find that you do not have the right data or the data is not clean. You may find that you don’t have the right skill sets to answer these questions or your BI system is not flexible enough. Your current status will begin to unfold and present itself, and you will begin to understand how far and how fast you need to move to achieve a long-term strategy. It will only take a few success stories to show the ROI and pave the way for a broader BI program in your finance department, or for your entire corporation.