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Big Brother really is watching you! Office 365 Delve

Under the name ‘Organizational Analytics’ the new version of Delve, available later this year, will include a dashboard view which will track your own work performance and compare it to the company average. Although Microsoft sees this as a valuable tool, one would question if it is an effective management tool or will upset the proverbial end user apple cart. This actually bothers me a bit. I realize that there are those who are diligent workers and then there are the slackers. Now we will all be tracked on exactly what we are doing, ‘oh-oh you went to too many meetings, you’re answering too many emails, the whole department is performing better than you’, I think you get the picture.

Another new feature, termed a productivity tool, Delve has also added a new profile page for users to specify their contact information, whom you report to, who reports to you, and, a personal blog page that enables the user to embed videos, documents and images. It also includes a Praise page where the user can list personal accolades, customer sales, contracts, whatever they wish to share with colleagues. Hmm, what will the Organizational Analytics think of my time spent building my blog of ‘atta boys’.

The above ‘tools’ go hand-in-hand with Microsoft’s new infographic, which I thought was just very tasteless. If you haven’t seen it yet, ‘This terrifying Microsoft ad suggests you’re not working hard enough in the bathroom‘ infographic, which has gone viral. I thought it was a huge marketing mistake, but am rethinking the assumption that it really wasn’t a mistake at all. What do you think?

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It’s Baaaaack. After a 30 year hiatus Artificial Intelligence is on the move.

I just read an interesting article, ‘The Return of Artificial Intelligence’. Written by Bloomberg News, it appears that the sleeping giant, Artificial Intelligence is now awake and on a roll. Most are start-ups, and according to the article, funding is there for the asking, without even a business plan.

So, what are these entrepreneurs developing? The current trend seems to focus on developing business tools that solve specific organizational challenges. Behind the resurgence, is companies like Amazon, Google, Apple, and Microsoft who have over the past decade deployed AI technologies, such as which ad is more likely to be clicked on. Other examples include Apple’s chirpy assistant, Siri, and Google’s self driving cars.

What I find interesting, is this focus on solving business problems. According to the article, “the University of California at San Francisco began working with Palo Alto, California-based MetaMind on two projects: one to spot prostate cancer and the other to predict what may happen to a patient after reaching a hospital’s intensive care unit so that staff can more quickly tailor their approach to the person. Theresa O’Brien, an associate chancellor at UCSF, said the university teamed up with the startup—the first such collaboration she’s aware of—because it wants to develop better approaches to bespoke medical treatment by employing computers to sort and link data, which AI can help.”

American Express uses AI to automatically detect fraudulent transactions. ““Our machine learning models help protect $1 trillion in charge volume every year, making the decision in less than 2 milliseconds,” Vernon Marshall, American Express’s functional risk officer, wrote in an e-mail, without disclosing which AI companies it works with. “We have been delighted with how well this technology can detect fraud.”

All in all, it will be curious to watch as AI developments unfold.

(If you have a few minutes and use SharePoint or Office 365, could you kindly take our metadata survey? You could win a free conference pass to Microsoft Ignite. We would greatly appreciate it)

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Delete Data? Why, just use search and create data lakes! Dive In!

I just read a very well written article, entitled Information Governance v Search: The Battle Lines Are Redrawn, by Ralph Losey, who is a practicing attorney and shareholder in a national law firm with 50+ offices and over 800 lawyers where he lead’s the firm’s Electronic Discovery practice group.

It is a very interesting viewpoint, and although the article is quite long, I would suggest reading it. Mr. Losey’s premise is that information should never be deleted and should be replaced with Artificial Intelligence search. He does make a several good points, but I guess I am still stuck in the old school on topics such as records management, information governance, and search. One of the points he makes is who is to decide when data has lost its value? This is referred to as an old-school problem, as in the new world all information should be saved and data lakes created, According to Losey, “information can prove what really happened in the past and can help you to make the right decisions. With smart search, there can be great hidden value in too much information. “I do take exception to that. There is quite a bit of information that organizations keep and is actually useless. Business users still spend much of their time searching because they can’t find what they need. Although, according to Losey, search will be so ‘smart’ that, I assume, the problem inherent in search engines will go away.

Losey concludes the article by stating, “that is the new reality of Big Data. It is a hard intellectual paradigm to jump, and seems counter-intuitive. It took me a long time to get it. The new ability to save and search everything cheaply and efficiently is what is driving the explosion of Big Data services and products. As the save everything, find anything way of thinking takes over, the classification and deletion aspects of IG will naturally dissipate. The records life-cycle will transform into virtual immortality. There is no reason to classify and delete, if you can save everything and find anything at low cost. The issues simplify; they change to how to save and search, although new issues of security and privacy grow in importance.” Where I see a problem is that organizations need to plan for the impact of collecting even more information, garbage or not. Not only in terms of hardware but in terms of keeping dark data.

For Information Governance, duplication and multiple sources of truth will be present. How are you certain the information you are basing decisions on is relevant and accurate? Just trust the search engine?

Perhaps from a legal standpoint, the organization does need to be more careful on delete versus keep. But not all data or content retains value forever. I wonder too, by keeping all data, eliminating records management, and depending only on search, does it impact the results of the data mining? Does it make data mining more complex to get to the information you are seeking as you are now dealing with a tremendous data set where you don’t really know which end is up? I would tend to think so.

Anyway, a radically different perspective. He hasn’t convinced me. What about you?

(If you have a few minutes and use SharePoint or Office 365, could you kindly take our metadata survey? You could win a free conference pass to Microsoft Ignite. We would greatly appreciate it)

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Will Enterprise Search and Text Analytics Become One Product? Good Luck!

Enterprise search has always been viewed by most as lacking in findability. According to statistics, business users still spend quite a bit of time every day searching for what they can’t find. What’s in the future? According to Grand View Research, and their industry analysis of the enterprise search market, enterprise search will grow to USD $5.02 billion by 2020, (hey, does anyone ever go back and check these predictions?). The growth can be attributed to the ‘need to manage large volumes of data efficiently in an organization so as to improve operational efficiency’. These enhancements are to include security.

According to the report, ‘the large enterprises segment is expected to dominate the market over the next six years, which can be credited to the need to search accurate data across a vast database’.

Although we are a search vendor, I can envision, in idea only, combining text analytics and enterprise search. Text analytics tools require a high level of expertise, currently uses a great deal of resources, both hardware and people, and results aren’t necessarily quickly delivered. Quite a big difference than whipping out a typical spreadsheet. Plus the amount of content is exploding every year. At some point, like now, it becomes unmanageable.

For this to happen, enterprise search better improve by leaps and bounds (not ours of course) and new analytics tools that are business user driven need to be developed. Maybe they are, and I just don’t know about them. On the negative side, most organizations do not manage their content proactively, some don’t even have search turned on, and some still lack the ability to integrate diverse repositories into a single user interface. If all this is to happen before 2020, I would say good luck. Someone has a lot to do.

(If you have a few minutes and use SharePoint or Office 365, could you kindly take our metadata survey? You could win a free conference pass to Microsoft Ignite. We would greatly appreciate it)

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Sometimes you just have to shake your head. A couple of the many problems of search.

Analysts, studies, surveys, consultants point to the problems of search – meaning no one can ever find what they need. Same old problem that has existed probably when search began. Management seems to be well aware of the challenges of search, understand what unstructured content is yet, most do nothing about it. There are not only pretty good search engines, there are tools, such as ours, that assist in eliminating most of the challenges with search.

Step back a minute. According to an AIIM presentation, Are You Prepared for Digital Disruption? 2015 Predictions:
• 71% of organizations search is essential, yet only 18% have cross-repository search capabilities
• 28% of organizations have not tuned or optimized their search tool at all, including 8% who have not turned it on

This is where I begin to shake my head and question if there is any gray matter left in management or IT. I’m not sure why, when the technology is readily available, that they don’t take a stab at solving basic problems. Only 18% have cross-repository search capabilities? Not productive, I’m sure it’s not user friendly, and costly to have business users wasting their time searching multiple repositories one-by-one. The second statement is why on earth would an organization think that a search engine was just plug-and-play. Many come close, but tuning and optimization can greatly improve search outcome. And finally, I did have to chuckle about the 8% who have not turned search on. Maybe they just don’t want to know the answers.

Anyone have any reasons for the above? I am clueless.

(If you have a few minutes and use SharePoint or Office 365, could you kindly take our metadata survey? You could win a free conference pass to Microsoft Ignite. We would greatly appreciate it)

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End User Considerations in Search – Really We Need to Think About Them?

Many individuals don’t know how to search, and using one or two word keywords they will expect the results to be what they were looking for. Too many results causes navigational difficulties and the inability to visually evaluate the results to discern which entry is closest to what the user was searching for. Providing detailed search criteria is an individual, and not necessarily logical choice. Although most search engines support Boolean expressions they are beyond the knowledge of most end users for query refinement. In addition, 33% have difficulty navigating/orienting search results and 28% have difficulty maintaining orientation on a website.

Interestingly, users tend to abandon the search if there are many results or too many pages. According to IDC, 85% of relevant documents are never retrieved during search. From a business user perspective, all of these behaviors are repeated in the organization. The only caveat is that business users will tend to search longer if they know the information is there. 55% of searchers selected irrelevant results from a list of query responses multiple times, 36% did not go beyond the first 3 search results – not pages…results on page 1, and 91% did not go beyond the first page of search results.

Our final challenge with search is how we look for information is quite different between people and between people and machines.

The search engine must accommodate the different ways that users search and be able to discern their intent – human and machine retrieval are very different. Humans are limited by their ignorance. We don’t know what we’re looking for much of the time and so do not know how to find it. We often rely on technology to provide parameters to narrow our scope and put us on the right track. Unfortunately, technology is “face value” and so it does not know how to interpret our queries. Unless trained, machines do not understand that we can have a single word mean multiple things (order a meal, put things in order) or multiple terms mean the same thing (star: celestial entity, celebrity).

(If you have a few minutes and use SharePoint or Office 365, could you kindly take our metadata survey? You could win a free conference pass to Microsoft Ignite. We would greatly appreciate it)

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Should search vendors go back to the basics? Or is it too late?

The very basics of search accommodate the different types of searches executed by business users. I think search vendors should go back to the basics. Although business users may be guru’s on using Facebook, Google search (doubt it), Pinterest, and the list goes on. They are not necessarily proficient when searching in the business environment.

There are three types of queries and we will take a look at each of them.

A searcher will use a Navigational Query when they know exactly the specific information they are seeking. In this case, there is usually ‘one’ right answer and the search will either return the correct results or not. For example, if the search was looking for “ROI for eMail Campaign on Data Privacy Webinar’, there is one right response and the selection list of similar documents would be very narrow.

Informational Queries are utilized to educate the searcher. In this type of query, the searcher is looking for answers or more details on a subject. For example a search on “Marketing Campaigns” will yield many results because it is a very broad keyword. In this case, the searcher is looking for knowledge on a particular topic and the results will lead to information that is relevant to the query.

Transactional Queries are goal orientated searches where the searcher has the intent to perform an action. For instance the searcher is looking for the right descriptors to add to a document of record, this would be a transactional query.

All types of searches must be considered in a search strategy. For the most part, users will employ all types of searches depending on the activity. Therefore the search interface must accommodate all options by using several techniques often using a hierarchy, which is especially useful for informational queries. Other techniques can be provided by the search engine to interact with the searcher to refine the results, such as faceted navigation. Auto-classification, taxonomies, and analytics tools are typically used to feed the output to the search engine index to improve relevancy and accuracy.

(If you have a few minutes and use SharePoint or Office 365, could you kindly take our metadata survey? You could win a free conference pass to Microsoft Ignite. We would greatly appreciate it)

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