As an industry, our data is a mess – not particularly helpful in terms of improving the quality of your management analytics. That may be an understatement. Let me give you a few examples.
Example #1: This past few weeks we have been working with a client on a shipping and handling study involving “free” shipping and what options to consider. The shipping station captures details about customer orders, products, revenue, costs (without accessorial charges), etc. But we can’t compare totals for orders, cartons shipped and costs between the shipping station, order management, accounting system and UPS’ internal shipping data.
Shipping expenses at most direct merchants are higher than all other fulfillment expenses combined including management, labor, facility costs and packing materials. But we need more accurate data to develop the strategy.
Example #2: How many times does this happen in your company? You go to a sales meeting and marketing says they think sales are up 3.5%, but the merchants say it’s really up 6.3%. The specific numbers in this example aren’t important; the point is that the two figures aren’t even close. That’s the reality in many companies today especially with online sales growth and disparate reporting systems. And it gets worse as we factor Google and website analytics into marketing decisions.
Example #3: Say management has tasked you with developing a report and you try to go back to plans and actuals from prior seasons, maybe from a couple years back. How many different versions of the sales, purchase and inventory plans and actuals are there? Which versions are the ones the company was managing to?
You get the picture. There isn’t a “single version of the truth,” one official set of figures for sales, inventory, plan and history in DTC operations. For management to have confidence in the integrity of the data they’re using, I think the time has come to advocate and budget for projects that resolve these problems. While not new problems, I believe they inhibit the effective management and growth of omnichannel businesses.
The problem is generally the same. They are many data fields in disparate systems with the same name – take for example sales. Is that flash sales before audited adjustments? Is it gross sales without being netted by returns? Or is it really gross demand, customer orders without cancellations and returns subtracted? Until you understand how the data is actually defined and you normalize it, you will have these discrepancies.
Your ERP may have a data warehouse but that doesn’t mean specific applications are defined for your purposes.
If you are trying to determine how data warehouses or business intelligence software could benefit your company, here are 5 things to help you determine if they’re right for your company:
Define the User Requirements
Find the ones that will have the highest payback and benefit. Recognize that OLAP, data warehouse and business intelligence tools are generally not designed to provide industry specific applications. This means your company needs to treat the endeavor more as a developmental project than implementing a commercial business application such as an OMS, WMS or ERP.
Identify the IT and Analyst Support Needed
Recognize that this type of systems project will require business analysts and IT support to define the application, normalize the data, build the data base and implement. Can this team define more effective management reporting to manage and grow your business?
Develop a Vendor Short List
Recognize there are dozens of vendors and systems available. This will require using a Request for Information (RFI) to get a ballpark estimate.
Estimate the Multi-Year TCO
Included in your total cost calculations should be the initial systems research; cost of selection; software license fees; initial software and hardware for development; rollout costs after the pilot phase; annual vendor support costs; and internal staffing costs.
What’s the ROI?
Does this level of investment and ongoing cost have an acceptable return on investment?
Our opinion is that for many companies it’s time to invest in making their management analytics much more effective, and in normalize the data and making it more accurate.
Curt Barry is Founder and President of F. Curtis Barry & Company