ERP: Enterprise Resource Planning
The use of desktop computers to download data from accounting systems or other operational systems has created access to reams of data relating to business operations. I have always been fascinated by the revelations this can provide.
The trick, however, is to consolidate and filter that data in order to see the trends and indicators of what is going on within the operations that leads to outliers appearing from time to time.
I was on the audit of Apple Australia when I had the opportunity to download the entire inventory file from their warehouse management system into an Excel file. Matching this data to usage by SKU data enabled me to see how many months' supply they had on hand of each item of inventory.
Although of interest as a one-off examination of inventory turns, which is fine in an audit context, as a CFO or procurement specialist you really want to prevent issues of excess inventory holdings. So good supply chain software should be set up to include usage data as part of its' re-order algorithm. And temper such automated process with information about EOL - end of life - knowledge for that part. There's no point in letting the system order a large number of parts that are about to be superseded by a new model.
In my role as a CFO, I have used ERP data in an environment where we had to reduce costs significantly - and quickly. Regional management had given my predecessor a list of names of headcount they wanted made redundant based solely on the total value of their salaries. I analysed the timesheet data within the ERP to discover which staff were still busy working on client billable work, and could not be let go without compromises to that delivery. This changed the list significantly and the response from Regional management was that this was "...the best report I have ever received from Finance...". The report became a regular management tool of the business, where we monitored Staff Utilisation by Employee by month, to check that everybody was keeping busy and earning their keep.
In one of my first roles after leaving the profession, the company decided to implement a new Oracle General Ledger system, including a global data warehouse. The data warehouse was a repository of every transaction processed through the Oracle GL, and included our invoices to customers, invoices from our suppliers, and project accounting data including every timesheet recorded by every employee worldwide, - this resource was a goldmine of financial data. Problem was, there was no front end or report writing capability implemented by the global team. They just gave us access to huge amounts of raw data.
In response, I sent two of my best and brightest on an advanced excel training course. They came back and shared an emerging technology with the rest of the team - the first pivot tables we had ever seen. By extracting the raw transactions from the data warehouse we were able to filter and present sales and cost of delivery by customer, by product line, and by client industry group (the matrix reporting used by the business). And of course, having access to timesheet data - what every employee in the workforce was doing every hour of the day - was mind-blowing. We could now really get an understanding of where our staff were spending their effort, and compare this to the fees that the clients were paying.
We were able to add revenue and profit by customer and by deliverable for each of the customer industry verticals across the business into our standard monthly reporting packs, in a format where the headline numbers could be drilled-down into by double-clicking on any item that piqued your interest. We subsequently shared this with the Global data warehouse team and they adopted it as one of the standard global front-end reports available within the system.
Key Metrics Reporting
Once the finance team has visibility to ERP data and consolidated it into useful information, it is then something that should be set up to be repeatable and automated, so you can monitor it over time with minimal effort.
As part of the Key Metrics reporting for the business, then, the executive should be provided with monthly inventory turnover metrics as an indicator of the good management of the procurement and inventory management function. Similarly, Days Sales Outstanding (DSO) is a key metric indicating the health of the accounts receivable function that should be reported monthly. Revenue per head is another metric I have shared with my ELT monthly. Whilst the detailed data behind it will be less useful to senior management, distilling the data down to a high-level indicator of health provides a quick measure of comfort that the basics of business management are being correctly executed by the team.
The Devil is in the detail
As you monitor summary metrics over time, you need to be able to dig into the source of the data, if any abnormality is observed. You don't want to go to the Board and say "we can see that X is up this month" and not have an answer when the inevitable question arises: "Why?".
A colleague at one business was impressed when I provided a report detailing Revenue By Customer in the monthly reporting pack, along with the P&L monthly reporting pack, in support of the figure showing our revenue variance to forecast. To me, it seemed a logical extension of the pack, but apparently it had never been shared before...
I have also been involved in numerous conversations where staff have disputed the financial reports. The reporting you are using to manage the business must be beyond reproach and entirely bullet-proof and trustworthy. You need to decide what is the Source of Truth, and ensure that all the BI reports you issue can be reconciled to that. In the above example, the revenue by client report would have to agree to the GL revenue reported in the P&L analysis. Having a report that enables you to go deep into the data to support the leading indicator is imperative to the credibility and reputation of the finance function. If not within the Board meeting, at least to be able to circulate separately, in support of your observations and recommendations.
Data Analysis as part of good governance
One of the assumptions within Six-Sigma and ACE performance improvement methodologies, is that if it isn't measured, then it's not going to be optimally controlled. I have seen this in many situations, especially when starting work at a new employer:- If the previous team did not monitor something, then it was bound to have stones un-turned.
Sloppy practices - such as not closing out WIP projects on a timely basis - led one business to have almost 1,000 jobs open when I commenced with them. With high-level, regular monitoring and proper management of the issue, I was able to correct this and close out all of the old projects without a significant hit to the P&L. This was a win, because every open project in the accounting system is an opportunity for costs to be incorrectly attributed and potentially lost from visibility.
Comments