Author Archives: thedoctor

Good SaaS vs. Bad SaaS

A recent post over on Richard Anson’s blog on “11 Crucial Tactics for SaaS Pricing”, while written for new SaaS vendors who need to know how to price their solutions, did a great job of helping to point out some of the key elements of a good SaaS solution sales process vs. a bad SaaS solution sales process as well as some key elements of a good SaaS solution from a customer’s perspective vs. a bad SaaS solution from a customer’s perspective.

In particular, it focusses in on some of the key non-functional characteristics that should be examined in your SaaS purchase process. These non-functional characteristics can easily be summarized in a quick side-by-side comparison of good SaaS vs. bad SaaS.

 

Good SaaS Bad SaaS
Value-based Cost-based
ROI-justification Process Improvement
Business Case Justification Potential Manpower Reduction
Priced According to Company Size and Utilization One Price Fits All
Competitively Priced Priced Out of the Ballpark

 

In other words, if the SaaS solution is good, it will be competitively priced, and priced according to your company size and intended utilization, come with a business case justification, deliver a proven ROI, and clearly deliver ongoing value.

And if a SaaS solution is bad (for you), it will be priced out of the ball-park with respect to its competition (and be either too expensive to deliver value or too cheap for the company to sustain over the long term, which will lead either to the provider’s failure or substantial price increases at contract renewal time), have little in the way of a solid business case justification, or have a poor ROI over the short and/or long term. SaaS is more than features, functionality, hands-off management, and a cool web experience — it’s about delivering value to your bottom line.

For insights on how to cost out the TCO of a SaaS solution, and compare that TCO to an installed solution, see SI’s classic post on Uncovering the True Cost of On-Premise Sourcing & Procurement Software. For insights on what constitutes a good SaaS contract, see SI’s classic posts on SaaS Contractual Considerations (Part I and Part II). And remember, as per SI’s recent post on Maximizing ROI from Technology, it doesn’t matter how strategic the IT Vendor is, it only matters how strategic the solution they offer is.

The First World Postal Services are in Trouble, But …

Royal Mail in the United Kingdom was founded in 1516.

The first post-master general was appointed in the US in 1775.

Canada Post was founded in 1867.

But yet it’s Canada Post that could be the postal service to show how struggling postal services may yet survive in the twenty-fist century!

As reported in this post over on The Economist Blogs, Canada Post, also looking at large pension shortfalls (to the tune of 6 Billion), is the first of the big postal services to make the drastic changes required to keep financially viable in the new world of online advertising, billing, and payments and private delivery services. It appears that Canada Post is going to be the first to eliminate home mail delivery — putting everyone on community mailboxes.

Home delivery to the 5 million households who still receive it will be phased out over four years, beginning in 2014. They will join the 3.8 million households that already go to a group mailbox to collect mail and parcels. (Canada’s remaining residents collect mail from building lobbies, public and private post offices, or rural mailboxes.)

Unfortunately, staying alive will also result in 8,000 postal workers being cut from a postal staff of 55,000. Hopefully the private parcel delivery services will continue to grow, especially with the growth of online commerce in Canada (led by Amazon and it’s recent introduction of its Prime Service in Canada), and pick up a large number of these displaced workers.

Now, the home mail delivery alone, estimated to save 500 Million a year, won’t make that much of an impact against a 6 Billion pension shortfall, but it’s a good start, especially if Canada Post’s savings projection of 700M to 900M a year by 2020, from all of the changes it plans to make, comes true.

Why Big Brains Will Beat Big Data in Procurement


Today’s guest post is from Ryann Kahn, Marketing and Communications Manager at Source One Management Services.

Two weeks ago, the Sourcing Innovation blog published an article about how the three cognitive traps stifle global innovation. I couldn’t help but think about how the same points could be made in procurement: data (though usually we don’t have Big Data) can help overcome some common issues, but ultimately Big Brains are more important and effective at the same job.

Take a procurement sourcing project for example.

The commonly used traditional three-bid process is data driven. It implies that if you collect enough (i.e. three pieces of) data, then you are making a good decision. Now, by collecting three bids, you know you are not getting the worst price and service out there and you are encouraging some competition. But without category expertise or a strategic process in place, can you really consider the data alone enough to justify that you have made a wise and innovative decision? Data != strategic sourcing.

But the data itself can often lead to the confirmation bias that the doctor referenced previously. Was your RFP template (or software solution) structured in a way that drove you to the conclusion that you already had envisioned? For example, if you want to remain with your local incumbent supplier, does your scorecard penalize suppliers for not having a location near you? Did you only request pricing on a specific product, which you knew your preferred supplier had the best (or only) price available? Confirmation bias in the sourcing world is real and common. Many companies effectively eliminate competition with better solutions because of the way they structure their questions.

By contrast, a true strategic sourcing process uses data in a Big Brain process.

The first step is a spend analysis of data from contracts, supplier invoices, P-Cards, supplier reports, POs, and more. (That’s a lot of data.) Then we look at market intelligence, historical trending, new products or process enhancements and benchmark data. (Now that’s Big Data!) All of this information is pulled, assessed, and analyzed. But the data alone does not give a full picture of a company’s spend. It takes the “curious, open mind” to uncover the whole story. Data may suggest inadequacies, but only through more in-depth research and thorough interviews with stakeholders and end users will one be able to identify problems and usage requirements.

The next step of the strategic sourcing process is the sourcing strategy. Again, it begins with data collection to cast a wide net of suppliers and determine their capabilities. But the bulk of the work in this stage belongs to the Big Brain: creating the supplier strategy, envisioning an RFx strategy, and planning for an execution strategy.

Even if procurement evolves to join the Big Data bandwagon, data will never be able to replace a human category expert. A category expert comes armed with nuanced knowledge of market trends, characteristics, players, and history, and uses analytical skills to apply that to plain data. Or, as the HBR article says, “When we look at markets different from our own we often have little information”. An expert who has been intimately involved with sourcing a category for years will be able to achieve better results than a novice armed with data, or the most powerful e-sourcing tool, any day.

In the final phases of the strategic sourcing process, implementation and compliance, it is entirely the work of a Big Brain. Experts must ensure that a company is actually achieving the results that were identified in the earlier phases in terms of savings and level of service. These experts may use tools to help collect the data to support the process, but the tools themselves don’t do an adequate job of capturing the data that is important to the unique organizational situation.

Data can, and does, help make good sourcing decisions, but ultimately it’s the Big Brains that lead the way. A Big Brain will always be needed to strategically apply the data (big or small), and be the “curious, open-minded researcher” to make a good decision.

Thanks, Ryann.