FeaturedEnterprise Search, Knowledge Management, & Customer Service: Some of the Study Stuff Ups Evident?
One of my two or three readers sent me a link to “The 10 Stuff Ups We All Make When Interpreting Research.” The article walks through some common weaknesses individuals make when “interpreting research.” I don’t agree with the “all” in the title.
This article arrived as I was reading a recent study about search. As an exercise on a surprisingly balmy Sunday afternoon in Kentucky, I jotted down the 10 “stuff ups” presented in the Interpreting Research article. Here they are in my words, paraphrased to sidestep plagiarism, copyright, and Google duplication finder issues:
- One study, not a series of studies. In short, an anomaly report.
- One person’s notion of what is significant may be irrelevant.
- Mixing up risk and the Statistics 101 notion of “number needed to treat” gets the cart before the horse.
- Trends may not be linear.
- Humans find what they want to find; that is, pre existing bias or cooking the study.
- Ignore the basics and layer cake the jargon.
- Numbers often require context. Context in the form of quotes in one on one interviews require numbers.
- Models and frameworks do not match reality; that is, a construct is not what is.
- Specific situations do matter.
- Inputs from colleagues may not identify certain study flaws.
To test the article’s premises, I I turned to a study sent to me by a persona named Alisa Lipzen. Its title is “The State of Knowledge Management: 2014. Growing role & Value of Unified Search in Customer Service.” (If the link does not work for you, you will have to contact either of the sponsors, the Technology Services Industry Association or Coveo, an enterprise search vendor based in Canada.) You may have to pay for the report. My copy was free. Let’s do a quick pass through the document to see if it avoids the “stuff ups.”
First, the scope of the report is broad:
1. Knowledge management. Although I write a regular column for KMWorld, I must admit that I am not able to define exactly what this concept means. Like many information access buzzwords, the shotgun marriage of “knowledge” and “management” glues together two abstractions. In most usages, knowledge management refers to figuring out what a person “knows” and making that information available to others in an organization. After all, when a person quits, having access to that person’s “knowledge” has a value. But “knowledge” is as difficult to nail down as “management.” I suppose one knows it when one encounters it.
2. Unified search. The second subject is “unified search.” This is the idea that a person can use a single system to locate information germane to a query from a single search box. Unified suggests that widely disparate types of information are presented in a useful manner. For me, the fact that Google, arguably the best resourced information access company, has been unable to deliver unified search. Note that Google calls its goal “universal search.” In the 1980s, Fulcrum Technologies (Ottawa, Canada) search offered a version of federated search. In 2014, Google requires that a user run a query across different silos of information; for example, if I require informatio0n about NGFW I have to run the query across Google’s Web index, Google scholarly articles, Google videos, Google books, Google blogs, and Google news. This is not very universal. Most “unified” search solutions are marketing razzle dazzle for financial, legal, technical, and other reasons. Therefore, organizations have to have different search systems.
3. Customer service. This is a popular bit of jargon. The meaning of customer service, for me, boils down to cost savings. Few companies have the appetite to pay for expensive humans to deal with the problems paying customers experience. Last week, I spent one hour on hold with an outfit called Wellcare. The insurance company’s automated system reassured me that my call was important. The call was never answered. What did I learn. Neither my call nor my status as a customer was important. Most information access systems applied to “customer service” are designed to drive the cost of support and service as low as possible.
“Get rid of these expensive humans,” says the MBA. “I want my annual bonus.”
I was not familiar with the TSIA. What is its mission? According the the group’s Web site:
TSIA is organized around six major service disciplines that address the major service businesses found in a typical technology company.
Each service discipline has its own membership community led by a seasoned research executive. Additionally, each service discipline has the following:
- Focused research agenda
- Dedicated research team
- Benchmark study
- Dedicated track at Technology Services World conferences
- Member Advisory Board
In addition, we have a research practice on Service Technology that spans across all service discipline focus areas.
My take is that TSIA is a marketing-oriented organization for its paying members.
Now let’s look at some of the the report’s key findings:
The people, process, and technology components of technology service knowledge management (KM) programs. This year’s survey examined core metrics and practices related to knowledge capture, sharing, and maintenance, as well as forward-looking elements such as video, crowd sourcing, and expertise management. KM is no longer just of interest to technical support and call centers. The survey was open to all TSIA disciplines, and 50% of the 400-plus responses were from groups other than support services, including 24% of responses from professional services organizations.
InterviewsElasticsearch: A Platform for Third Party Revenue
Making money from search and content processing is difficult. One company has made a breakthrough. You can learn how Mark Brandon, one of the founders of QBox, is using the darling of the open source search world to craft a robust findability business.
I interviewed Mr. Brandon, a graduate of the University of Texas as Austin, shortly after my return from a short trip to Europe. Compared with the state of European search businesses, Elasticsearch and QBox are on to what diamond miners call a “pipe.”
In the interview, which is part of the Search Wizards Speak series, Mr. Brandon said:
We offer solutions that work and deliver the benefits of open source technology in a cost-effective way. Customers are looking for search solutions that actually work.
Simple enough, but I have ample evidence that dozens and dozens of search and content processing vendors are unable to generate sufficient revenue to stay in business. Many well known firms would go belly up without continual infusions of cash from addled folks with little knowledge of search’s history and a severe case of spreadsheet fever.
Qbox’s approach pivots on Elasticsearch. Mr. Brandon said:
When our previous search product proved to be too cumbersome, we looked for an alternative to our initial system. We tested Elasticsearch and built a cluster of Elasticsearch servers. We could tell immediately that the Elasticsearch system was fast, stable, and customizable. But we love the technology because of its built-in distributed nature, and we felt like there was room for a hosted provider, just as Cloudant is for CouchDB, Mongolab and MongoHQ are for MongoDB, Redis Labs is for Redis, and so on. Qbox is a strong advocate for Elasticsearch because we can tailor the system to customer requirements, confident the system makes information more findable for users.
When I asked where Mr. Brandon’s vision for functional findablity came from, he told me about an experience he had at Oracle. Oracle owns numerous search systems, ranging from the late 1980s Artificial Linguistics’ system to somewhat newer systems like the late 1990s Endeca system, and the newer technologies from Triple Hop. Combine these with the SES technology and the hybrid InQuira formed from two faltering NLP systems, and Oracle has some hefty investments.
Here’s Mr. Brandon’s moment of insight:
During my first week at Oracle, I asked one of my colleagues if they could share with me the names of the middleware buyer contacts at my 50 or so named accounts. One colleague said, “certainly”, and moments later an Excel spreadsheet popped into my inbox. I was stunned. I asked him if he was aware that “Excel is a Microsoft technology and we are Oracle.” He said, “Yes, of course.” I responded, “Why don’t you just share it with me in the CRM System?” (the CRM was, of course, Siebel, an Oracle product). He chortled and said, “Nobody uses the CRM here.” My head exploded. I gathered my wits to reply back, “Let me get this straight. We make the CRM software and we sell it to others. Are you telling me we don’t use it in-house?” He shot back, “It’s slow and unusable, so nobody uses it.” As it turned out, with around 10 million corporate clients and about 50 million individual names, if I had to filter for “just middleware buyers”, “just at my accounts”, “in the Northeast”, I could literally go get a cup of coffee and come back before the query was finished. If I added a fourth facet, forget it. The CRM system would crash. If it is that bad at the one of the world’s biggest software companies, how bad is it throughout the enterprise?
Stephen E Arnold, July 2, 2014
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