Author: Lynda Moulton (Page 7 of 18)

This is an interesting topic for two reasons: there is enormous diversity in the ways we all think and go about finding content; personalizing a search interface without being intrusive is extremely difficult. Any technology that requires us to do activities according to someone else’s design, which bends our natural inclination, is by definition not going to be personal.

This topic comes to mind because of two unrelated pieces of content I read in the past 24 hours. The first was an email asking me about personal information management and automated tagging, and the second was an interview I read with Mike Moran, a thought leader in search and speaker at one of our Gilbane Conferences. In the interview, Mike talks about personalized search. Then Information Week referenced search personalization in an article about a patent suit against Google.

Here is my take on the many personalized search themes that have recently emerged. From dashboards to customizing results, options to focus on particular topics or types of content, socialized search to support interacting with and sharing results, to retrieving content we personally created or received (email), content we used or were named in, all might be referred to as search personalization. Getting each to work well will enhance enterprise search but….

Knowing how transient and transformative our thoughts and behaviors really are, we should focus realistically on the complexity of producing software tools and services that satisfy and enhance personal findability. We are ambiguous beings, seeking structured equilibrium in many of our activities to create efficiency and reduce anxiety, while desiring new, better, quicker and smarter devices to excite and engage us. Once we achieve a level of comfort with a method or mechanism, whether quickly or over time, we evolve and seek change. But, when change is imposed on an unprepared mind, our emotions probably override any real benefit that might be gained in productivity. Then we tend to self-sabotage the potential for operational usefulness when an uncomfortable process intrudes. Mental lack of preparedness undermines our work when a new design demands a behavioral shift that lacks connection to our current state or past experiences. How often are we just not in a frame of mind to take on something totally alien, especially with deadlines looming?

Look at the single most successful aspect of Google, minimalism in its interface. One did not need to wade through massively dense graphics scrambled with text in disordered layouts to figure out what to do when Google first appeared. The focus was immediately obvious.

I am presenting this challenge to vendors; there is a need to satisfy a huge array of personal preferences while introducing a minimal amount of change in any one release. Easy adoption requires that new products be simple. Usefulness must be quickly obvious to multiple audiences.

I am presenting this challenge to technology users; focus your appetite. Decide before shopping or adopting new tools what would bring the most immediate productivity gain and personal adoptability for maximum efficiency. Think about how defeated you feel when approaching a new release of an upgraded product that has added so many new “bells and whistles” that you are consumed with trying to rediscover all the old functions and features that gave your workflow a comfortable structure. Think carefully about how much learning and re-adjusting will be needed if you decide on technology that promises to do everything, with unlimited personalization. It may be possible, but does it really feel personally acceptable.

It takes patience, knowledge and analysis to tell when search is really working. For the past few years I have seen a trend away from doing any “dog work” to get search solutions tweaked and tuned to ensure compliance with genuine business needs. People get cut, budgets get sliced and projects dumped because (fill the excuse) and the message gets promoted “enterprise search doesn’t work.” Here’s the secret, when enterprise search doesn’t work the chances are it’s because people aren’t working on what needs to be done. Everyone is looking for a quick fix, short cut, “no thinking required” solution.

This plays out in countless variations but the bottom line is that impatience with human processing time and the assumption that a search engine “ought to be able to” solve this problem without human intervention cripple possibilities for success faster than anything else.

It is time for search implementation teams to get realistic about the tasks that must be executed and milestones to be reached. Teams must know how they are going to measure success and reliability, then to stick with it, demanding that everyone agrees on the requirements before throwing the towel in at the first executive anecdote that the “dang thing doesn’t work.”

There are a lot of steps to getting even an out-of-the-box solution working well. But none is more important than paying attention to these:

• Know your content
• Know your search audience
• Know what needs to be found and how it will be looked for
• Know what is not being found that should be

The operative verb here is to know and to really know anything takes work, brain work, iterative, analytical and thoughtful work. When I see these reactions from IT upon setting off a search query that returns any results: “we’re done” OR “no error messages, good” OR “all these returns satisfy the query,” my reaction is:

• How do you know the search engine was really looking in all the places it should?
• What would your search audience be likely to look for and how would they look?
• Who is checking to make sure these questions are being answered correctly
• How do you know if the results are complete and comprehensive?

It is the last question that takes digging and perseverance. It is pretty simple to look at search results and see content that should not have been retrieved and figure out why it was. Then you can tune to make sure it does not happen again.

To make sure you didn’t miss something takes systematic “dog work” and you have to know the content. This means starting with a small body of content that it is possible for you to know, thoroughly. Begin with content representative of what your most valued search audience would want to find. Presumably, you have identified these people through establishing a clear business case for enterprise search. (This is not something for the IT department to do but for the business team that is vested in having search work for their goals.) Get these “alpha worker” searchers to show you how they would go about trying to find the stuff they need to get their work done every day, to share with you some of what they consider some of the most valuable documents they have worked with over the past few years. (Yes, years – you need to work with veterans of the organization whose value is well established, as well as with legacy content that is still valuable.)

Confirm that these seminal documents are in the path of the search engine for the index build; see what is retrieved when they are searched for by the seekers. Keep verifying by looking at both content and results to be sure that nothing is coming back that shouldn’t and that nothing is being missed. Then double the content with documents on similar topics that were not given to you by the searchers, even material that they likely would never have seen that might be formatted very differently, written by different authors, and more variable in type and size but still relevant. Re-run the exact searches that were done originally and see what is retrieved. Repeat in scaling increments and validate at every point. When you reach points where content is missing from results that should have been found using the searcher’s method, analyze, adjust, and repeat.

A recent project revealed to me how willing testers are to accept mediocre results when it became apparent how closely content must be scrutinized and peeled back to determine its relevance. They had no time for that and did not care how bad the results were because they had a pre-defined deadline. Adjustments may call for refinements in the query formulation that might require an API to make it more explicit, or the addition of better category metadata with rich cross-references to cover vocabulary variations. Too often this type of implementation discovery signals a reason to shut down the project because all options require human resources and more time. Before you begin, know that this level of scrutiny will be necessary to deliver good-to-great results; set that expectation for your team and management, so it will be acceptable to them when adjustments are needed for more work to be done to get it right. Just don’t blame it on the search engine – get to work, analyze and fix the problem. Only then can you let search loose on your top target audience.

When thinking about some enterprise search use cases that require planning and implementation, presentation of search results is not often high on the list of design considerations. Learning about a new layer of software called Documill from CEO and founder, Mika Könnölä, caused me to reflect on possible applications in which his software would be a benefit.

There is one aspect of search output (results) that always makes an impression when I search. Sometimes the display is clear and obvious and other times the first thing that pops into my mind is “what the heck am I looking at” or “why did this stuff appear?” In most cases, no matter how relevant the content may end up being to my query, I usually have to plow through a lot (could be dozens) of content pieces to confirm the validity or usefulness of what is retrieved.

Admittedly, much of my searching is research or helping with a client’s intranet implementation, not just looking for a quick answer, a fact or specific document. When I am in the mode for what I call “quick and dirty” search, I can almost always frame the search statement to get the exact result I want very quickly. But when I am trying to learn about a topic new to me, broaden my understanding or collect an exhaustive corpus of material for research, sifting and validating dozens of documents by opening each and then searching within the text for the piece of the content that satisfied the query is both tedious and annoyingly slow.

That is where Documill could enrich my experience considerably for it can be layered on any number of enterprise search engines to present results in the form of precise thumbnails that show where in a document the query criterion/criteria is located. In their own words, “it enhances traditional search engine result list with graphically accurate presentation of the content.”

Here are some ideas for its application:

• In an application developed to find specific documents from among thousands that are very similar (e.g. invoices, engineering specifications), wouldn’t it be great to see only a dozen, already opened, pages to the correct location where the data matches the query?
• In an application of 10s of thousands of legacy documents, OCRed for metadata extraction displayable as PDFs, wouldn’t it be great to have the exact pages of the document that match the search displayed as visual images opened to read in the results page? This is especially important in technical documents of 60-100 pages where the target content might be on page 30 or 50.
• In federated search output, when results may contain many similar documents, the immediate display of just the right pages as images ready for review will be a time-saving blessing.
• In a situation where a large corpus of content contains photographs or graphics, such as newspaper archives, scientific and engineering drawings, an instantaneous visual of the content will sharpen access to just the right documents.

I highly recommend that you ask your search engine solution provider about incorporating Documill into your enterprise search architecture. And, if you have, please share your experiences with me through comments to this post or by reaching out for a conversation.