October 26, 2015
Sources of differentiation
Obviously, a large fraction of what I write about involves technical differentiation. So let’s try for a framework where differentiation claims can be placed in context. This post will get through the generalities. The sequels will apply them to specific cases.
Many buying and design considerations for IT fall into six interrelated areas:
- Scope: What does the technology even purport to do? This consideration applies to pretty much everything. 🙂
- Usually, this means something like features.
- However, there’s an important special case in which the important features are the information content. (Examples: Arguably Google, and the Bloomberg service for sure.)
- Accuracy: How correctly does the technology do it? This can take multiple forms.
- Sometimes, a binary right/wrong distinction pretty much suffices, with an acceptable error rate of zero. If you’re writing data, it shouldn’t get lost. If you’re doing arithmetic, it should be correct. Etc.
- Sometimes, there’s a clear right/wrong distinction, but error rates are necessarily non-zero, often with a trade-off between the rates for false positives and false negatives. (In text search and similar areas, those rates are measured respectively as precision and recall.) Security is a classic example. Many other cases arise when trying to identify problems or
- Sometimes accuracy is on a scale. Predictive modeling results are commonly of that kind. So are text search, voice recognition and so on.
- Other trustworthiness.
- Reliability, availability and security are considerations in almost any IT scenario.
- Also crucial are any factors that are perceived as affecting the risk of project failure. Sometimes, these are lumped together as (part of) maturity.
- Speed. There’s a great real and/or perceived “need for speed”.
- On the user level:
- There are many advantages to quick results, “real time” or otherwise.
- In particular, analysis is often more accurate if you have time for more iterations or intermediate steps.
- Please recall that speed can actually have multiple kinds of benefit. For example, it can reduce costs, it can improve accuracy, it can improve user experience, or it can enable capabilities that would otherwise be wholly impractical.
- There can also be considerations of time to (initial) value, although people sometimes overrate how often this is a function of the technology itself.
- Consistency of performance can be an important aspect of product maturity.
- On the user level:
- User experience. Ideally, using a system is easy and pleasurable, or at least not unpleasant.
- Ease of use often equates to ease of (re)learning …
- … but there are exceptions, generally for what might be considered “power users”.
- Speed and performance can avoid a lot of unpleasant frustration.
- In some cases you can compel somebody — usually an employee — to use your interface. Often, however, you can’t, and that’s when user experience may matter most.
- An important category of user experience that doesn’t directly equate to ease or is Of course, the more accurate the recommendations are, the better.
- Most systems have at least two categories of user experience — one for the true users, and one for the IT folks who manage it. The IT folks’ experience often depends not just on true UI features, but on how hard or difficult the underlying system is to deal with in the first place.
- Cost, or more precisely TCO (Total Cost of Ownership). Cost is always important, and especially so if there are numerous viable alternatives.
- Sometimes money paid to the vendor really is the largest component of TCO.
- Often, however, hardware or IT personnel expenditures are the lion’s share of overall cost.
- Administrators’ user experience can affect a large chunk of TCO.
Related links
- This post is starting out with two sequels, on data management and business intelligence respectively.
- Issues of differentiation are central to my strategic worksheet.
- When thinking about differentiation, keep in mind the distinction between wants and needs.
- This post fits well with my claim that every product in a category is positioned along the same set of attributes.
- In a post last year about differentiation, I wrote “Your spiffy innovation is important in fewer situations than you would like to believe.”
- If you think you’re a rare exception to that rule, please see my post about over-optimism. 🙂
Categories: Buying processes, Predictive modeling and advanced analytics, Pricing, Text
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[…] the previous post I broke product differentiation into 6-8 overlapping categories, which may be abbreviated […]