Overview
ERP (Enterprise Resource Planning) systems continue to proliferate across the landscape of most businesses. The promise of ERP was that a single software system could be used up and down the organization to tie together all the disparate parts of a business whether it be finance, sales, purchasing, inventory, operations, etc. and allow them access to the information in the ERP system to be accessible to all of these different parts of the organization. As the cost of the underlying hardware and software supporting an ERP system has declined this has enabled businesses of all types to implement and leverage this technology.
ERP vendors pride themselves in providing a multitude of functional modules to support all the different areas of the business. The dirty secret of many ERP systems is that they were designed to be transactional systems and not analytical systems. The type of data a transactional system collects and manages is very different from an analytical system. Below is a table that compares some of the differences:
Transactional Systems vs Analytical Systems
| Data / Usage Characteristics | Transactional Data | Analytic Data |
| Source | The laborers and automated systems of the company | The ERP system |
| Timeliness | Input in real-time as the activity occurs | Requires a historical perspective over hours, days, weeks, months, and years |
| Perishability of Data | Valuable during the period in which the transaction occurs | Value increases over multiple time horizons |
| Data Structures | Normalized / optimized for performance | Star Schema / designed to permit views of the data from different perspectives |
| Performance | Requires instantaneous performance to avoid work slowdowns | Less performance-critical / focused on providing insights to complex interdependencies |
| Users | The hourly employees | The management team |
| Use Cases | Entering in of transactions such as orders, estimates, purchase orders, job completions, received goods, transfers, etc. | Extracting data on metrics of the organizations such as sales backlog, production backlog, purchase orders acknowledged, products shipped, etc. |
Reporting Impact
How do these differences impact the ability of an organization to glean actionable information from their ERP system? Primarily in that reports and managerial level data cannot be extracted directly from the transactional data. The transactional data needs to be reformatted, aggregated, summarized, normalized, and cross-referenced in a way that makes sense to the business. This need became apparent in the early days of ERP systems in the 1970’s and 80’s and led to the subsequent creation of data warehouses which provided a platform on which to report data beyond the operational minutiae of normal transactions. But these data warehouses were not in and of themselves the answer as they required tools which could extract and present the data from these data warehouses in an understandable form. Over time these tools have come to be known as Business Intelligence (BI) tools.
Effective Reporting Requirements
Combining these two together, data warehouses and BI tools then become the sine qua non or basic cost of entry for effective business reporting from an ERP system. What does this mean and more importantly what are the costs and capabilities that an organization must possess to effectively use these tools and extract actionable business-relevant insights from the ERP system? To achieve this an organization must possess or acquire several areas of knowledge and expertise to develop effective reporting from their ERP system. We will examine these below:
Tools
· A Data Warehouse – Whether this is simply a database created to hold the analytic data or a specialized database custom tailored to support what is called Online Analytics Processing (OLAP), an investment has to be made here. Simply running against the ERP system’s production data will negatively impact performance and limit the ability to see the data in a business relevant form. This cost can vary widely from around $100 a month to over $1,000 a month depending on the organization’s size and the data warehouse selected.
· A BI Tool – This is a tool that enables the extraction and presentation of the data from the data warehouse in a graphical or tabular form. There is a broad spectrum of tools available here that range in cost from around $100 a month to over $1,000 a month
Domain Expertise
· Technical ERP Expertise – To be able to create a data warehouse and report from that data warehouse, a technical depth of knowledge of the ERP system is needed. That knowledge would have to include the terms and naming conventions used in the ERP system and also knowledge of the underpinning database’s structure. tables and data elements. If this expertise is already available in-house the cost my be nominal, but if hired from the outside would probably amount to at least $1,000 per month
· Business Domain Expertise – Knowledge of the various processes and business practices within the organization is also required. If it is a manufacturing organization then this knowledge would include a comprehension of such things as Bills of Material, Job Steps, Operations such as machining, deburring, grinding, milling, assembly, etc., Quality processes, and component knowledge. This expertise typically exists within the organization but must be combined with the BI Tool (see below) knowledge to be effective
· BI Tool Expertise – A knowledge of the BI tool being used and how it extracts information from the data warehouse and presents it is a keystone needed for effective reporting. This knowledge has to be trained into users in the organization or hired from the outside. The cost is most likely to be at least $1,000 per month if hired.
Labor
· People – No matter what the tool selected there is a need to have someone leveraging the Domain Expertise described above to actually create the reports. If the Domain Expertise exists all in one person all the better. If not, there is a definite learning curve required as that person will need to understand the various aspects of the other domains and how to synthesize that into meaningful reports. This area is difficult to quantify but there is industry data available that indicates a simple report takes about 8 hours of labor to construct a simple report and about 3 times that long for a complex report. In an organization that is looking for 5 simple reports a month and 3 complex reports a month (i.e. 96 reports in the course of a year) that translates into 112 hours a month. At a conservative IT resource burdened cost of $50 per hour that would translate in $5,600 per month.
Summary
In this document we have looked at the hidden cost of reporting from an ERP system. Many organizations assume the cheapest most cost-effective approach to this is to buy a tool and Do It Yourself (DIY). This DIY approach overlooks the cost in hardware and software to establish the appropriate data warehouses and acquire the BI tools for the report creation. It also ignores the domain expertise required in three widely disparate areas 1) the ERP system 2) the business operation itself and 3) the BI tool. Rarely do these 3 areas of expertise exist in one person in the organization and often have to be developed through training and long-term exposure or simply “rented” by hiring an outside expert. Lastly the time commitment of what it takes to create a report is often overlooked. Once simple reports are created those in the business often ask for more complex reports that involve considerably more time to create beyond a simple report.
We applied a fairly conservative model to estimate what these actual costs might be. Our estimate though somewhat crude is quite conservative with the actual cost having a potential to be much higher. Our estimate showed that it could cost an organization somewhere between $5,800 and $7,800 per month or $69,600 to $93,600 per year to provide reports from their ERP system.
Although reporting is sometimes an afterthought in many organization’s ERP plans, the opposite should actually be true. What value is it for an organization to create a system in which large portions of the organization spend their entire working day feeding information into, without an appropriate and effective reporting capability to understand and act on what all that information means?
In summary, a DIY approach can end up costing an organization a significant amount in hidden costs plus in many ways it is not effective or ends up taking considerable time to be effective. A better approach would be to hire an organization that doesn’t require you to acquire any additional tools, already has the appropriate expertise in multiple domains, and has already built out business relevant reports based on actual business requirements. That would be us, IntelliDash, please reach out to us today so we can show you the value we have already built into our “Analytics As A Service” platform.
