As I go around different organisations looking at their information systems and how they manage, analyse and use their data, there are a number of common themes which breed success. In some of my previous posts I’ve talked about how important it is to build a data driven culture; to employ the right people; and how important it is to build analytics and business intelligence upon a solid information management platform. All of these things are true — and in many cases not that much different from success in other areas of business. But today I want to share some of my thoughts and observations about the beauty of an amazing User Exerience and how a well designed and constructed user experience and user interface can increase information quality and convey decision information.
Improving Information Quality
I’ll start with what is arguably the most important aspect of information management — ensuring the accuracy of information. Accuracy of information is critical for any information system, as without trust in the information being provided it is impossible for analytics and ultimately business intelligence to succeed.
While a huge body of work is devoted to using machine learning and statistical methods to reduce the impact of incorrect information from users, one of the most surprising things I’ve observed about well designed systems is their use of visual cues to users to reduce user error. This isn’t just a minor observation — in an article by Oleysa Krysynyak entitled ‘How to Save Lives by Reducing User Interface Errors’, links are made between UI design and providing fast, reliable and easily understood information to doctors, literally saving lives!
Visual cues provide almost unnoticed pathways for users to enter information. Things like consistent color schemes (i.e. red is always bad, green is always good), consistent transactional interactions and a commitment to a reduction in clutter all contribute to providing a seamless experience for users and induce far less errors. As a result computing resources are freed up and the analytics and business intelligence which supports decision making increases in impact.
This is a non-trivial challenge. In teams I have worked with in the past, up to 50% of our time was spent working through each user interaction and relating it back to common themes we wanted to convey. Often times we would find that much of our programming construct needed to be changed to simplify variables and data tables, further refining our data sets and assumptions about users. In turn, this would create further discussion about how we wanted to convey information. Yet by sweating each detail of the user experience, and bringing an unrelenting commitment to convey information clearly to users, we would come up with sometimes amazingly simple answers to complex problems. The beauty of this kind of user experience is that the quality of the information being gathered is increased without the user even being aware of what is happening!
Decision Quality Impact
My second observation about well designed systems is their ability to convey often complex and comprehensive data to users in a manner they can understand and react too.
For me, this was bought home on a system I worked on which displayed some performance metrics for a platform. A previous organisation had come in and could track all sorts of interesting things — the uptime of each platform, the performance of different components for each platform and how frequently this had contributed to success. Yet as my team and I started to work through the consultation process with users, we quickly discovered that the presentation of this data wasn’t helping users at all. What they really wanted to know was which components failed the most, which components contributed the most to cost, and which stuff was going to be the most critical for them to solve. All of this information (other than the finance data) had already been gathered by the previous organisation, but it wasn’t helping the users of the system. As a result, the quality of their decision making hadn’t improved.
In contrast, great information systems come up with innovative ways to take a broad series of data sets, combine them together and present the results to users. In many cases, these teams behind these information systems end up finding solutions which are so simple in their elegance, and so well presented in the User Interface that their end users are entirely abstracted from the complexity of the problem!
This kind of User Experience is beautiful in its ability to allow individuals to focus on their own areas of expertise. Programs like Tableau and Highchartsallow User Experience designers to present complex information sets in a simple way. In turn, this allows users to use their expertise to contribute to the organisation. This in turn allows managers to know what is important and so on. The end result? Users are able to make accurate, timely decisions from the data being presented.
Users Don’t Hate the IT System
My final point in this post is one of my pet passions — building systems which actually help users. Far too often I see organisations which spend millions on marketing, talk a great game to customers and then punish their employees with substandard DOS based, text driven systems which require an intimate knowledge of search strings and building SQL queries to actually get information out of it.
These kind of back end systems don’t help users or customers at all, and almost always the outcome is counterproductive to the organisations goals. If users of the system hate it, they won’t use it to get good information, won’t be able to help their customers and they will figure out ways around it. As a result, the analytics of the information system reduce in quality, the organisation cannot get good business intelligence and everyone loses. All because someone somewhere didn’t take the time to get it right.
In contrast, great information systems become a tool to help users access the information they need to do what they’re doing better, faster, easier. When users don’t hate their IT system, everyone wins and a positive feedback loop is introduced. It’s definitely worth it!
So What To Do Now?
In my opinion, building a simple, elegant User Interface and User Experience is one of the great contributers to Information System success. I am constantly challenged in my work to keep refining systems, and often this refining starts with looking at how the user is presented, conveyed and interacts with data. It’s a time consuming process and while many people try to short cut the process, I’ve never found a way to do so without compromising effectiveness. For me there is no substitute for reading about psychology, learning to really listen to users and gaining an intimate knowledge of the goals of an organisation and what matters to them. I would challenge those who are reading this article to take the time to get this right. Take the time to support those UX designers in your team who really do sweat the detail, or, if you are one of those designers, I would challenge you take the time to keep investing in this area. In doing so, you’ll build information systems which will transform organisations into in the Information Age!!!
I hope this article has helped, and as always, please feel free to contact me on LinkedIn, Facebook, Twitter or in the comments below.
The Great User Challenge
You’ve drunk the Cool Aid, caught the dream, understand the vision. After many months of consideration and research, brainstorms and meetings with stakeholders, you’re ready to launch into analytics and bring your organisation into the Information Age. You know it’s going to take time, but you’ve invested in your leadership team and are building a data driven culture, backed by a cohesive data driven team. Funds are set aside for the change, and you’ve now become one of the agents for positive change in a data driven world.
So now you ask: Where to start?
Todays post is about answering this question and I’m going to look at three areas:
The User Concept
As always, the start of the answer is a discussion about the concept of Information Management and Analytics, both of which feed Business Intelligence.
Conceptually, Information Management is about people. In fact, if you abstract it a bit further, information itself is about people. From the perspective of business, all information is gathered, analysed and distributed to increase the efficiency and effectiveness of business. From this perspective, the discussion quickly becomes about how a user can measurably benefit an organisation, rather than being a problem which needs to be solved.
To further distil this concept, I offer this definition of a user:
Any person who regularly interacts with an information system.
There is no distinction here about internal and external users, nor is there any reference to automated trawlers of an information system (also known as bots). This is deliberate as an information system should to be built to provide a seamless connection between customers, clients, employees and managers. When any of these groups (or malicious users) choose to use automated methods to trawl information, the information system should be capable of handling this.
For many organisations, this concept is not new. It’s been used successfully in customer service, product selection and is a straightforward application of the laws of supply and demand. However, the application of this concept to information systems is almost unheard off.
Consider this: Almost every organisation in the world (outside of tech paradises like Silicon Valley and New York) uses Microsoft Word, Excel and Powerpoint to store, write and analyse information in various formats. Even when an organisation uses a backend system like SAP to start combining their information stores together, often times this is copied and pasted out of the ‘Datamart’, transferred into one of these applications and then shared via email.
Take a few moments to consider the time inefficiencies this introduces to workflow. Each point of interaction introduces delays, replication and error, all of which are considered necessary by the users of the system to do their job. As multiple departments get involved, the situation continues to get worse. Before you know it, people are creating spreadsheets to store their own little information empires (I call them spreadmarts), introducing macros…the list goes on.
The User Framework
In contrast today, I present a more excellent way. I call it ‘The User Framework’.
The User Framework is based around three assumptions:
There’s some interesting points to be drawn from this:
Firstly, any information system which uses this framework needs extra storage capacity. This is not actually a problem, and I’ll cover why in the technical part of this post.
Secondly, such an information system will change over time. Tracking what a user does and then analysing this to find efficiencies can provide some pretty radical results. For instance, when you find that a user is accessing a particular information daily, you can drastically increase efficiency by surfacing this information sooner, reducing search time. This is not to mention the efficiencies in being able to preprocess results.
Thirdly, this kind of information system creates an iterative improvement framework, where it gets better and better over time. This is important as it allows an organisations competitive advantage continue to improve.
This kind of system is incredibly empowering and enabling for organisations. Over time and with the right team, the quality of data will improve as will the analytics being performed. Furthermore, as the analytics team continues to go deeper into process flows and outcomes, the requirement for information will be refined, leading to a higher quality of business intelligence.
A post like this would not be complete without some mention of the technical aspects of such a proposal. I will state up front that I receive no commission from these mentions; these are just tools I have used and/or know and am impressed with.
In mentioning these things, I want to be clear that each organisation will take a different path to Information Management. I’ve worked with companies who outsource almost all of this stuff, through to ones who choose to do it entirely in house. I have also personally worked on building aspects of these systems, and it takes a while. As such, the mix of products you choose to do these things will be individual - however, I also believe the products mentioned below will meet almost every organisations needs.
I have also witnessed some pretty poor advice being given by software/hardware vendors in the past. Any organisation or IT staff who claims that increasing storage capacity or server power is difficult is not telling the truth. If you get this, find a good company to help you (like mine)!!!
Storage - Red Hat
This is becoming more and more of an issue. Many organisations are stuck using proprietary systems which charge astronomical amounts of money for adding storage and server capability. In my honest opinion, a better way forward is to look into the many products Red Hat offers. Not only is their code open sourced, they have a long history of figuring out ways to take legacy programs and import them with no loss of data.
Web Backend - Django or Ruby on Rails
Most organisations around the world are starting to realise that the most efficient way to create this kind of information system is using an internal web server of some kind. Both Django and Ruby on Rails are open source with massive communities.
Analytics Language - Python
There’s a lot of debate about this in the analytics world. My personal preference is Python, simply because its so broad. Furthermore, Python integrates with Red Hat and Django seamlessly, which for an end to end solution is pretty powerful.
Server Stuff - Red Hat Linux
I love analysing data. I've done it for nearly 10 years now in various shapes and forms, and for me it's an endless world of wonder. There's nothing else I'd rather be doing!