Or, in other words, “How do you apply the application standards to improve findability to applications built by third-party providers who do not follow your standards?”
I’ve previously written about the standards I’ve put together for (web-based) applications that help ensure good findability for content / data within that application. These standards are generally relatively easy to apply to custom applications (though it can still be challenging to get involved with the design and development of those applications at the right time to keep the time investment minimal, as I’ve also previously written about).
However, it can be particularly challenging to apply these standards to third-party applications – For example, your CRM application, your learning management system, or your HR system, etc. Applying the existing standards could take a couple of different forms:
The rest of this post will discuss a solution for option #3 above – how you can implement a different solution. Note that some search engines will provide pre-built functionality to enable search within many of the more common third party solutions – those are great and useful, but what I will present here is a solution that can be implemented independent of the search engine (as long as the search engine has a crawler-based indexing function) and which is relatively minimal in investment.
So, you have a third party application and, for whatever reason, it does not adhere to your application standards for findability. Perhaps it fails the coverage principle and it’s not possible to adequate find the useful content without getting many, many useless items; or perhaps it’s the identity principle and, while you can find all of the desirable targets, they have redundant titles; or it might even be that the application fails the relevance principle and you can index the high value targets and they show up with good names in results but they do not show up as relevant for keywords which you would expect. Likely, it’s a combination of all three of these issues.
The core idea in this solution is that you will need a helper application that creates what I call “shadow pages” of the high value targets you want to include in your enterprise search.
Note: I adopted the use of the term “shadow page” based on some informal discussions with co-workers on this topic – I am aware that others use this term in similar ways (though I don’t think it means the exact same thing) and also am aware that some search engines address what they call shadow domains and discourage their inclusion in their search results. If there is a preferred term for the idea described here – please let me know!
What is a shadow page? For my purposes here, I define a shadow page as:
To make this solution work, there are a couple of minimal assumptions of the application. A caveat: I recognize that, while I consider these as relatively simple assumptions, it is very likely that some applications will still not be able to meet these and so not be able to be exposed via your enterprise search with this type of solution.
Given the description of a shadow page and the assumptions about what is necessary to support it, it is probably obvious how they are used and how they are constructed, but here’s a description:
First – you would use the query that gives you a list of targets (item #2 from the assumptions) from your source application to generate an index page which you can give your indexer as a starting point. This index page would have one link on it for each desirable target’s shadow page. This index page would also have “robots” <meta> tags of “noindex,follow” to ensure that the index page itself is not included as a potential target.
Second – The shadow page for each target (which the crawler reaches thanks to the index page) is dynamically built from the query of the application given the identity of the desirable search target (item #3 from the assumptions). The business rules defining how the desirable target should behave in search help define the necessary query, but the query would need to contain at minimum some of the following data: the name of the target, a description or summary of the target, some keywords that describe the target, a value which will help define the true URL of the actual target (per assumption #1, there must be a way to directly address each target).
The shadow page would be built something like the following:
The overall effect of this is that the search engine will index the shadow page, which has been constructed to ensure good adherence to the principles of enterprise search, and to a searcher, it will behave like a good search target but when the user clicks on it from a search result, the user ends up looking at the actual desired target. The only clue the user might have is that the URL of the target in the search results is not what they end up looking at in their browser’s address bar.
The following provides a simple example of the source (in HTML – sorry for those who might not be able to read it) for a shadow page (the parts that change from page to page are in bold):
<body> <div style="display:none;"> <h1>title of target</h1> description of target and keywords of target </div> </body> </html>
A few things that are immediately obvious advantages of this approach:
There are also a number of issues that I need to highlight with this approach – unfortunately, it’s not perfect!
There you have it – a solution to the exposure of your high value targets from your enterprise applications that is independent of your search engine and can provide you (the search administrator) with a good level of control over how content appears to your search engine, while ensuring that what is included highly adheres to my principles of enterprise search.
So we get to the exciting conclusion of my essays on the inclusion of employees in enterprise search. If you’ve read this far, you know how I have characters the first and second generation solutions and also provided a description of a third generation solution (which included some details on how we implemented it).
Here I will describe what I think of as a fourth generation solution to people finding within the enterprise. As I mentioned in the description of the third generation solution, one major omission still at this point is that the only types of searches with which you can find people is through administrative information – things like their name, address, phone number, user ID, email, etc.
This is useful when you have an idea of the person you’re looking for or at least the organization in which they might work. What do you do when you don’t know the person and may not even know the organization in which they work? You might know the particular skills or competencies they have but that may be it. This problem is particularly problematic in larger organizations or organizations that are physically very distributed.
The core idea with this type of solution is to provide the ability to find and work with people based on aspects beyond the administrative – the skills of the people, their interests, perhaps the network of people with which they interact, and more. While this might be a simplification, I think of this as expertise location, though that, perhaps, most cleanly fits into the first use case described below.
Some common use cases for this type of capability include:
This capability is something that has often been discussed and requested at my current employer, but which no one has really been willing to sponsor. That being said, I know there are several vendors with solutions in this space, including (at least – please share if you know of others):
A common aspect of these is that they attempt to (and perhaps succeed) in automating the process of expertise discovery. I’ve seen systems where an employee has to maintain their own skill set and the problem with these is that the business process to maintain the data does not seem to really embed itself into a company – inevitably, the data gets out of date and is ill-maintained and so the system does not work.
I can not vouch for the accuracy of these systems but I firmly believe that if people search in the enterprise is going to meet the promise of enabling people to find each other and connect based on of-the-moment needs (skills, interests, areas of work, etc), it will be based on this type of capability – automatically discovering those aspects of a worker based on their work products, their project teams, their work assignments, etc.
I imagine within the not too distant future, as we see more merger of the “web 2.0″ functionality into the enterprise this type of capability will become expected and welcome – it will be exciting to see how people will work together then.
This brings to a close my discussion of the various types of people search within the enterprise. I hope you’ve found this of interest. Please feel free to let me know if you think I have any omissions or misstatements in here – I’m happy to correct and/or fill in.
I plan another few posts that discuss a proof of concept I have put together based around the ideas of this fourth generation solution – look for those soon!
In my last post, I wrote about what I termed the first generation and second generation solution to people search in enterprise. This time, I will describe what I call a “third generation” solution to the problem that will integration people search with your enterprise search solution.
This is the stage of people search in use within my current employer’s enterprise.
What I refer to as a third generation solution for people search is one where an employee’s profile (their directory entry, i.e., the set of information about a particular employee) becomes a viable and useful target within your enterprise search solution. That is, when a user performs a search using the pervasive “search box” (you do have one, right?), they should be able to expect to find their fellow workers in the results (obviously, depending on the particular terms used to do the search) along with any content that matches that.
You remove the need for a searcher to know they need to look in another place (another application, i.e., the company’s yellow pages) and, instead, reinforce the primacy of that single search experience that brings everything together that a worker needs to do their job.
You also offer the full power of your enterprise search engine:
Below, you will find a discussion of the implementation process we used and the problems we encountered. It might be of use to you if you attempt this type of thing.
Before getting to that, though, I would like to discuss what I believe to be remaining issue with a third generation solution in order to set up my follow-up post on this topic, which will describe additional ideas to solving the “people finder” problem within an enterprise.
The primary issue with the current solution we have (or any similar solution based strictly on information from a corporate directory) is that the profile of a worker consists only of administrative information. That is, you can find someone based on their name, title, department, address, email, etc., etc., etc., but you can not do anything useful to find someone based on much more useful attributes – what they actually do, what their skills or competencies are or what their interests might be. More on this topic in my next post!
Read on from here for some insights on the challenges we faced in our implementation of this solution. It gets pretty detailed from here on out, so you’ve been warned!
Having written previously about my own principles of enterprise search and then some ideas on how to select a search engine, I thought it might be time to back up a bit and write about what I think of as “enterprise search”. Perhaps a bit basic or unnecessary but it gives some context to future posts.
For me, the factors of a search solution that make it an enterprise solution include the following:
The user interface to access the solution is available to all employees of the company.
This has the following implications:
The content available through the solution covers all (relevant) content available to employees
This has the following implications:
The other half of your enterprise search solution will be the search engine itself. There are plenty (many!) options available with a variety of strengths and weaknesses. I think if you plan to implement a truly enterprise search, the above list of content-based considerations should get you thinking of all of the places where you may have content “hiding” in your organization.
From that list, you should have a good sense of the volume of content and the complexity of sources your search will need to deal with.
Once you have a tool, you “just” need to apply the proper amount of elbow grease to get it to index all of the content you wish and present it in a sensible way to your users! No big deal, right?