Search. One of the most powerful changes in experience we’ve seen for the last 10-15 years. It is interesting, but search was with us many years. Search or find was a functionality in every enterprise application already 20-25 years ago. However, before Google made us to believe and experience the power of web search, the importance of this function was clearly underestimated. Because of Google wide adoption, we associate almost everything in search innovation with Google. It is not unusual to hear that vendor or developer is comparing what they do in search with Google.
Interesting enough, search innovation happens outside of Google Headquarters too. Old article from 2007 – Top 17 Search Innovations Outside Of Google speaks about it. Have a read, compare your notes from 2007 and draw your opinion. Several innovation mentioned in the article aree very resonating with PLM, engineering and manufacturing. The following two are my top choices – result refinement and parametric search. Here are passages I captured:
Results refinement and Filters: Often a natural next step after a search is to drill down into the results, by further refining the search. This is different from the “keyword-tweaking” that we’ve all gotten used to with Google; it’s not just experimenting with keyword combinations to submit a new query, but rather, an attempt to actually refine the results set [akin to adding more conditions to the “where” clause of a SQL query] – this would allow users to narrow the results and converge on their desired solution.
Parametric search: This type of search is closer to a Database query than a Text search; it answers an inherently different type of question. A parametric search helps to find problem solutions rather than text documents. For example, Shopping.com allows you to qualify clothing search with a material, brand, style or price change; job search sites like indeed let you constrain the matches to a given zip code; and GlobalSpec lets you specify a variety of parameters when searching for Engineering components (e.g. check out the parameters when searching for an industrial pipe ). Parametric search is a natural feature for Vertical Search engines.
Another interesting writeup that drove my attention last week was LinkedIn post – The Changing Face of Exploratory Search. Daniel Tunkelang, speaks about modern trends in search, such as entity-oriented search, knowledge-graph and search assistance. The conclusion Daniel made in his article is that future of search is in combination of faceted search and search assistance. He called it exploratory search. I found the following quotes very insightful:
Exploratory searcher has a set of search criteria in mind, but does not know how many results will match those criteria — or if there even are any matching results to be found.
Combining entity-oriented search and knowledge graphs has led to the use of faceted search interfaces that expose entities to searchers and encourage searchers to combine entities into precise search queries.
Search assistance offers the promise of making faceted search more accessible to the average searcher, enabling searchers to compose faceted search queries as they type. Indeed, search assistance makes it possible to expose untrained searchers to a richer set of relationships than typical faceted search interfaces, approaching the expressiveness of a database query language like SQL. Facebook’s Graph Search offers a taste of what is possible by combining faceted search with search assistance. It encourages people to create structured queries inside the search box, using suggestions along the way to guide the process of query construction.
PLM vendors are looking towards how to provide search as part of user experience. For most of user today, search is a natural part of application. At the same time, engineering and manufacturing data is semantically rich and interconnected. The complexity of products is growing. Product configurations, bill of materials, suppliers, manufacturers and many other data islands. All together creates a complex data access problem.
What is my conclusion? Customer demands is to have simplicity of Google combined with the complexity of product configuration, multiple bill of materials, variety of document configurations, manufacturing and supply data. The idea of “exploratory search” can be very compelling for engineering and manufacturing data. Just my thoughts…