ARC Advisory Group – October 23, 2015
To become agile, companies need to be transparent and use fast loops of observation, orientation, decision and action
Valentijn de Leeuw, ARC Advisory Group’s Vice President commented: “The combined strengths of MongoDB, inmation and Transpara results in an amazingly agile, scalable and easy to use operational data archive and easy to use operational intelligence tool. As an add-on cloud-based platform for visualization and analytics, it can offer complimentary added on top of other historian and visualization applications”. Read more…
As some of you have noticed when your iOS devices were recently upgraded from iOS 7.x to iOS 8.0, 8.0.1, and 8.1, logging into Visual KPI sites with authentication introduced some problems, including sites hanging and/or users being re-prompted for security credentials each time they click on something.
This has been reported many times now around the web and it appears to be an issue with iOS and specifically the Safari browser in these versions of iOS. Here are some links about it if you want to have a look yourself:
- iOS 8 Safari not working with sites using Windows Authentication (again)
- iOS 8 Safari Cannot Access Windows Authentication IIS websites
The good news is that in most cases (see the first link above – it’s complicated) upgrading it iOS 8.1.1 fixes the issue. Just today we ran a series of tests on the following iOS devices with Visual KPI to see where we stand:
- iOS 8.0 safari (any device) – failed
- iOS 8.0.1 safari (any device) – failed
- iOS 8.1 safari iPad 3 – failed
- iOS 8.1.1 safari iphone 6 – success
- iOS 8.1.1 safari iphone 5 – success
- iOS 8.1.1 safari iPad 3 – success
- iOS 8.3 safari iPhone 5 – failed on SSL (https://); success without SSL
- iOS 8.3 safari iPhone 6 – success (http:// and https://)
While not a complete set of tests (yet), we do know (and suggest) the following to resolve this while we wait for Apple to formally address the issue:
- iOS 8.1.1 appears to solve the issue for most devices (possibly not all). Please update your devices and let us know if you still see issues.
- Using Google Chrome instead of Safari works in all cases we have found
As always, we will monitor this closely with Apple and update you as they provide more information.
Yesterday, one of our great partners asked for some information about why we consider KPIs so important and why they are the cornerstone of our software. I figured it was time to really walk through this answer in detail and share our thoughts publicly. Off we go…
The main underlying value of using KPIs is their ability to compare apples to oranges. This can’t be emphasized enough.
KPIs are the fundamental basis for assessing the performance of an organization across any dimension, not just operations. A CEO cares about safety, profit, quality, efficiency, environmental and regulatory measures. Each of these measures uses different terminology and every individual measure within each category has its own units of measure, min, max, high, low, target (sometimes) – all different.
BUT, as soon as you make a single measure into a KPI, it is essentially “dimensionless” in that it can now be compared to every other KPI you have. It doesn’t matter if KPI 1 is Production Rate in mlb/hr and KPI 2 is Lost Time due to Accidents in days. Once they are KPIs they each can be seen as “Good” or “Not Good” and are now easily rolled up into an overall summary of how things are going across all dissimilar measures.
This is a qualitative rollup of quantitative data. Most execs care primarily about whether things are OK or not, and how they should be ready in case the phone rings and it is the EPA asking about their emissions at XYZ plant. They are going to know something is amiss at XYZ and how bad it is well before that phone call happens and without a single MEETING or phone call to the plant.
Visual KPI is uniquely positioned to deliver BOTH this qualitative executive view as well as the drill-down “what the hell is going on” type of analysis done by subject matter experts who are normally on the receiving end of phone calls from these same execs. Having the deep-dive data at their fingertips allows overworked and thinly stretched SMEs to be in many places at once, and still make fast, data-driven decisions based on the true details coming from the asset in question.
Organizations are all understaffed, and the normal behavior of humans when tasked with too much work, not enough time and an ever-dwindling quality of life and/or life balance are to simply do the minimum required for each task. The inevitable onset of humiliation and self-loathing which accompanies the knowledge that we are not doing our best work will eat at their soul and make them hate the company forcing them to be “checkbox” automatons just trying to work their daily task list to zero before another day starts with an all-new task list.
We can save them, their families, their jobs and cut down on turnover and employee dissatisfaction. In fact, we can restore humanity to its once optimistic and confident self! By creating corporate transparency through pervasive use of real-time, finger-tip available KPIs we can eliminate finger-pointing, reduce or eliminate status meetings, increase confidence in decisions made, reduce second-guessing, eradicate “information is power” cults of oppressors and increase corporate profits, customer satisfaction, regulatory compliance, safety and efficiency all without firing a single round or burning down a single building!
The secret is to tap all normally opaque data, craft the right KPIs out of all this shapeless unstructured chaos (Big Data, M2M and IoT being great examples), give the right data to the right people when they need it and at their fingertips, get out of their way and let them run the processes and assets the way they ALREADY KNOW how to do it. It’s not like the management wants to tell them HOW to do things, they just need to tell them WHAT result they are expecting. It’s the operations folks who REALLY know how to run things, and in the absence of ambiguous and contradictory demands from above, they can make their company a better place, with better results for all.
As a natural consequence, the corporation of the future will be a true meritocracy, with an almost complete transparency of operation in every dimension listed before – financial, environmental, operations, safety, quality, compliance. Visual KPI and KPIs in general, allow an enlightened company to truly empower its employees by GETTING OUT OF THE WAY. KPIs in every department ensure that every person KNOWS how they will be measured and rewarded. The result is a top-down driven strategy of WHAT and a bottom-up driven implementation of HOW. It is the only way to corporate nirvana.
P.S. If that isn’t a strong enough case or you want to see it from a functional level as well, here are some other benefits of using KPIs and Visual KPI:
- KPIs require almost no training to understand. KPIs have color, status and immediate meaning. On the flip side, analytics tools, data source specific tools and historian tools are ideal for admins, analysts and trained experts, but you wouldn’t just put that same depth of data or tools in front of executives or field staff – they just need answers. This also means you can put KPIs in front of a much larger group of users. Not just the data gurus or trained experts, but anyone who might benefit or be able to assist.
- KPIs provide the ideal basis for great alerting, or alerting in a common, scalable and understandable way.
- In a mobile setting (and really every setting nowadays), speed and clarity are everything. Having KPIs on a screen instantly draws your eye to the problem or opportunity and lets you zero in without having to sift through numbers.
Just a short post today to highlight an article we just read that shows how one of our favorite customers, Mohawk Paper, uses Visual KPI as the initial app of their BYOD (bring your own device) strategy for IT.
The article appears in Control Design this month and if you look closely you might notice some unfamiliar screenshots in the article. Consider that a teaser of what is coming very soon. If you want to hear about our next release as early as possible, subscribe for updates.
Check out the full article here: Mohawk Buys Into BYOD
Control Design for Machine Builders – May 7, 2014
By monitoring information from a wide array of processes, such as order entry, scheduling, inventory, production and industrial process control systems, Mohawk ensures the entire enterprise is constantly aligned and focused on key orders, priority requirements, last-minute changes and what’s happening on the production floor.
“This lets us respond rapidly to customers’ ever-changing requirements and market changes,” Stamas says. “The implementation of Visual KPI improved the quality and timeliness of our decision-making in manufacturing and maintenance processes and enhanced our responsiveness to customer requirements and manufacturing issues due to real-time access to machine, production and order status.” Read more…
Two of the hottest enterprise markets are about to collide. What does that look like and more importantly, what should it look like?
In our last post we looked at how historians and Big Data are aligned (quite well) and we have discussed all over this blog how to best mix historians and mobility. Now let’s look at Big Data as a larger concept and talk about what is possible, what is likely and what we feel is the right approach (for now).
Spoiler Alert! Mobile applications should only show results and analytics from Big Data that meet the characteristics of mobile user behavior in general.
This cannot be overstated and applies to all data, not just Big Data. Real humans use their phones and tablets in very specific ways and at very specific times, which is why you see common characteristics show up in almost all of the top mobile apps (business or consumer). Here are a few:
- Small chunks – break data into small, actionable parts I can work with on a small screen or with limited time. Analyzing wildly complex pivots of historical data on the train or waiting for the DMV is not the key use case here.
- Timely – show me what is happening right now or just happened in case I need to take action. Mobile is usually not the case to do deep analysis into the past or the future
- Context – give me more than numbers and pretty charts. Tell me if they are good or bad without me doing all of the work (KPIs are good for this)
- Location-aware – where something is happening may be just as important as its severity. Am I close to the problem and can I fix it?
- Alerts – the application should tell me when I should look at it, just like SMS, email or Facebook badges do.
We’ve probably all seen videos and software demos from the big BI vendors (SAP comes to mind) that show the CEO clicking a few buttons on their iPad to crunch some huge big data numbers from multiple angles to solve a wild problem right in front of the board of directors, but let’s be realistic. The data guys will always be called upon to solve these issues and they will most likely do this on the desktop. Not because of technical limitations, but because it makes sense.
Mobile BI in general often reminds me of a quote from comedian Patton Oswald that goes, “We’re science: all about coulda, not about shoulda.” We consistently see what people can do on mobile devices, but after talking to hundreds (probably thousands) of customers we’ve seen a distinct pattern emerge for what people should, or want to do. Just like with email, Facebook, Twitter, Google Maps, banking apps and more, mobile users want to know what is happening right now and what they can do about it. They are constantly checking feeds and stock prices, getting directions to their next appointment, etc. This behavior must be applied to mobile BI apps to be truly useful.
We must learn from Facebook, Twitter, email and other mobile success stories to really see what subset of Big Data will be useful to mobile users.
Hopefully you are seeing the answer already. Some of the best Big Data tools like Splunk, Cloudera, Pivotal and many others are doing a great job helping you get answers from huge, diverse data sets. Like BI vendors, they also may have mobile versions of their desktop applications, but as we’ve discussed this isn’t where success will be found because the behavior doesn’t match the feature set.
The ultimate first task is to refine those answers down to the ones that make sense to show mobile users and let them drill in only when necessary. For the moment, this lends itself most to operations and other fast-moving data, where people need to be alerted on a pending crisis, or know when inventories are low, or see what they should work on next based on their location. To get this right for a large number of users, and preferably those without extensive training, you need to surface only those items that match mobile user behavior.
As always, we’ll have more on this topic soon. Let us know what you think!
We get questioned a lot about both historians and big data, and since our team works with both (and many other types of data) we thought we should add our perspective to help clear up, or further muddy, the topic of Big Data.
First, let’s get our head around big data with some definitions from around the web:
- Wikipedia: Big Data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data in a single data set.
- Gartner: Big data is high-volume, -velocity and -variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.
- McKinsey: “Big data” refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze. This definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big data—i.e., we don’t define big data in terms of being larger than a certain number of terabytes (thousands of gigabytes).
For the purposes of answering how Big Data and Enterprise Historians relate, I think it is best to not just look at the size of the data (which is huge no matter how you look at it – see graphic below), but the characteristics of the data and the tools necessary to get value from it.
This is best summed up in a free guide from our friends at GE (makers of the Proficy Historian) called “The rise of Industrial Big Data.” They offer quite a few insights and detail about the size of historian data, the speed at which it moves, and much more. Here is a graphic from the guide that shows the data output of just one single factory area for example:
So we know historian data is big and has high velocity, but what really makes historian data fit the category of big data is how unique the tools are for storing, retrieving and analyzing this data. By the simple fact that historians are their own category and that most successful historians (OSIsoft PI, GE Proficy, Wonderware Historian, Rockwell FactoryTalk, Etc.) are not based on relational databases or data warehouses demonstrates just how specialized these tools must be.
So, is there any importance to putting historians in the Big Data category? Does it even matter? I think the answer is yes, for several reasons:
- Historians are not as well know as they should be. They have been around for decades but are only known to a small subset of the technology world and have remained stuck in a narrow band of industrial uses for far too long. Attaching them to the ‘hotness’ of the Big Data category may shine some light on these powerful engines and the value they bring.
- Historians bring some history and deep experience to the world of Big Data. Tens of thousands of companies run historians, and some historian customers have been running their systems for decades and have real knowledge that should be shared with the Big Data community.
- Many of the tools that were brought up in the historian age could translate very well to the Big Data age and more people need to know about them.
In our next post about big data we will explore how two giant and fast-growing industry topics are set to collide: Big Data & Mobility.
Until next time…
On Monday of last week, a group of security researchers discovered and publicly disclosed a vulnerability in OpenSSL, a software package that is widely used to secure online communications. They called the bug Heartbleed, which you can read about more at http://heartbleed.com/.
Transpara does not use, and has not used, OpenSSL with our software or on our wwebsite so we were not vulnerable to this bug. As an Visual KPI user, there is no need to take any action unless you have added OpenSSL to you own environment outside of our software.
We have also investigated the services we use, such as our web site and many other services. It appears that all of these services have either fixed the bug or were immune to this issue by not using OpenSSL. Therefore, we do not believe that any data has been accessed. We are actively monitoring the situation and will notify you if the situation changes in any way.