There were a swarm of papers published in the late 90′s and early 2000′s surrounding a very, very strange thing: turns out that asking people to fill out a survey about a positively viewed product actually causes them to buy more of that product, buy it more quickly, and become more profitable customers. This is called, in some circles, the “Mere Measurement effect.”Just in case you want to know where I came up with the above, here’s some light bedtime reading: Applied Stochastic Models in Business and Industry.
There are a slew more articles on the subject, a quick perusal on Google Scholar will get you acquainted with the literature.
There’s an older observation related to this new research: “What gets measured generally gets done.” Named for the place where studies were done on production improvements in the 1920′s, The Hawthorne Effect has now been evolved into multiple lines of research and nuance, but the point is simple: paying attention to things improves their performance.
Although today some research points to the fact that only measuring things does not necessarily improve them, the fact remains that measurement is vital to increased performance, especially as a form of attention given to a vital area. If you consider that timing a race is the only way to determine if one has run faster, and that looking at splits or heart rates or pace are also helpful to athletes in a training situation, it is obvious that measurement is a key to improved performance.
So how does Business Intelligence and the software industry as a whole make use of this?
Simple: turns out that any software that measures something, and shows that measurement, and interim measurements, to the people performing that behavior, will cause improvement against those measures. If that software shows those results publicly, or allows them to be discussed, things get even better.
We all see this is enterprise software sales, especially on inside sales teams, where the bell gets rung for each deal, where whiteboards show bookings quarter-to-date, and indeed in the entire performance monitoring industry.
If software not only measured those results, but also caused salespeople to think through and state their intentions (commits) and focus on the growth toward their intentions (pipeline), especially if we view the changes over time, the above research gives us a clear indication that sales performance would improve.
Oddly enough, if we stick with the sales performance theme, we find that most people use a CRM package to look at actual results (bookings) and usually pipeline. But almost all CRM packages don’t show changes in pipeline over time, or bring the key measures that matter to the fore, and track them over time.
This is echoed through most software packages: measurement is for managers – but that’s actually the place where it does the least good.
I say: Measurement for the masses!
I am sitting in salesforce.com’s partner conference right now. They just went through some great coverage about where they are working, where the opportunity is for partners, and where salesforce.com intends to build. They were open about what they were doing, and that is a great thing for partners, who want to make safe investments.
They also highlighted some interesting cases where salesforce has sold nearly 40,000 seats to a Japanese firm, but not for the CRM – but rather for the platform!
Which brings up another point: they are redubbing the platform as “the force.”
Good branding. Now if they could only change their ticker
All that ribbing aside,Â SaaS is going through an inflection. Business Objects’ Steven Lucas last night at the “after dark” party said that they have reached 50k subscribers, which is a big amount of recent growth. Salesforce’ platform sale is a huge unprecedented event.
So all that makes me more excited than ever about Mashups and the Mashup Exchange.
And if you’re looking for funding, look to Emergence Capital, a 5-year old VC that is tightly focused on SaaS, and is looking to invest in “technology-enabled-service” which includes BPO’s, information services companies, and SaaS.Â They are looking for people to build standalone companies, and are asking themselves the question: when will the force platform be ready for people to build on it?
Things are heating up.
Was doing some research and came across this post by Tom Davenport of Harvard’s Business School. In the post he postulates that the next big thing will be analytics @ the enterprise level.
The idea, or concept, of analytics, is a very good one. And the technology is getting there, but there are many problems, some that are intractable. Here are the obstacles:
1. Data Integrity and Unified Schema
There are many organizations that are working on this problem, but there are precious few enterprises anywhere in the world that have the right data infrastructure to actually know that their data is the right data that a manager is after, and even fewer that can tie data across the silos that are modern management systems. For instance, a company uses SAP for X and PSFT/ORCL for Y, and it will be yet another failed data warehouse installation that will solve the problem of how all the data in one system relates to the other.
There are small companies that are working on this problem, but it’s far from solved.
2. Behavior and Management skills
Even if the above problems were tackled and solved, and people could get access to the data they needed, there is a general paucity of good sense around what those numbers mean, and how they affect the business.
3. Lack of data on external benchmarks
Knowing what your company is doing, without an easy way to get access to external data to validate that position, leaves you with a limited understanding of the world and your place in it.
I recently assisted an organization that attempted to discover their penetration into a certain software market. They bucketed their revenues by the type of development environment that the products were sold into, and concluded that they had a fairly good mix of product sales. I asked them what the baseline was for those development environments in the marketplace. They researched the penetration of the various development environments, and then superimposed their revenue shares against the relative market shares of the development environments, and suddenly a very different picture emerged: what seemed like a good mix in the absence of context turned into a lopsided distribution when weighed against the market.
It is almost impossible to readily find good data, at the line manager level, around the baseline market conditions, and it is even more difficult to know how to interpret data well, and to understand the causality or relationship between data.
In the next 3 years, even at the highest enterprise levels, the gut instinct and intuition are going to be better methods than crunching the numbers.
Had a very stimulating strategy session today with a start-up. They were interested in talking about partnership, but we quickly started into talking about corporate strategy.
Partner strategy is an outgrowth of a solid corporate strategy. If you think you’ve got a good corporate strategy, ask yourself how it instructs your alliances or partnership strategy. If the corporate strategy can’t guide and inform the partner strategy, it’s back to the drawing board on the corporate strategy.
But partnership really is simple.
1. Make a list of what you want
2. Make a list of what others want
3. Make a list of what you’re willing to give, and how much.
4. Figure out where the intersections are in 1, 2, and 3.
Simple huh? But it’s not.
Many startups latch on to a partner in order to quickly grow a business. Pretty soon, the partnership takes over the startup! The solution: write down at the outset what you want to achieve, and revisit that written description from time to time. See if you’re boiling the frog (the market) or if you’re being boiled.
Boil or be boiled. Now that’s simple.