Utilize the data you have to accurately determine your initial costs and payoff period – before you commit.
As the demands of the industry evolve, investing in technology solutions becomes a requirement to stay competitive and scale. A common challenge for any operation looking to evolve their business is determining which investments to prioritize, often based on ROI. Vendor sales organizations have a tendency to optimize the advertised ROI based on hypothetical information instead of real data. ROI based on educated guesswork is going to make any decision based on it risky at best — and calamitous at worst.
Beware the Vendor’s Hypothetical ROI Numbers
For example, we worked with a company who spent over $50 million on an automation system. The projected ROI from the system vendor, using their hypothetical values, showed a 5-year ROI, making it seem like a reasonable investment. However, once the system was implemented, the consequences of hypothetical ROI calculations were revealed. Using Easy Metrics Cost to Serve analytics, we found that the cost of the revised labor needs from the automation was almost double what was projected. This pushed the ROI (without interest costs) to over 20 years. The company subsequently went bankrupt and dissolved over this ill conceived investment.
Many of our customers have large networks of distribution centers, and the technologies used within these centers are highly varied. With Easy Metrics advanced analytics, we are able to show cost to serve and performance comparisons across the network. Using this data we can identify which of those technology investments are generating strong ROI, and which facilities could benefit from those investments. Additionally, by benchmarking these technology profiles we are able to recommend which technology initiatives should be implemented at specific facilities based on cost to serve and volume metrics. Easy Metrics doesn’t use hypotheticals — it uses concrete data.
As part of the Easy Metrics OpsFM Maturity Curve, we are able to guide companies through their technology strategy with objective data and ROI analysis. Companies will often voice concern that the workflow types across their network are too variable to conduct such an analysis. This is not the case. The Easy Metrics data model continues to grow; we are able to normalize your data against benchmarked data across our extensive customer base.
Download the PDF: Normalizing Process Data
Cross Facility Comparisons and Benchmarking
An accurate ROI calculation starts with identifying a problem, quantifying it, and then quantifying the realistic and expected metrics once the new solution is in place. There are two ways of analyzing cost and efficiency opportunities for your processes: cross facility comparisons and industry benchmarks.
For facility networks with varying technologies, you can compare the process cost and performance based on the technologies used.
In the given example we can see that Seattle, which uses voice pick, runs a cost per line about 20% lower than Phoenix (Seattle $0.20/line and Phoenix $0.25 per line), which has RF Scan, when normalized for wage variances. Based on unit volumes in Phoenix, the $200k investment in voice pick will return its investment through process savings in about 18 months.
Another approach is to model your data based on industry benchmarks for various technologies and then calculate potential ROI for such process technology investments. Easy Metrics does this algorithmically by analyzing all of your process data and then running it against technology benchmarks to flag processes where such an investment might achieve a strong ROI.
Easy Metrics is uniquely capable of helping you apply the real data from your facilities in your technology ROI assessments. If you’d like to learn more, download our Normalizing Data Solutions Brief or schedule a call with one of our operations analytics experts.
