Thursday, April 24, 2014

The Promise of Self Serve

How many times in your life have you had an excellent experience with self service? The vending machine saves a lot of time in standing in line and making a transaction with a cashier. This is something that we all understand and take for granted. We are all familiar now with self service gasoline stations, but can you remember what it was like the first time you pumped your own gas? Do you remember the days before online banking? The first iterations of online banking were very cumbersome, with 3rd party software required to connect and non-intuitive interfaces. There is definitely a learning curve for the consumer when adopting self service, and we ignore this fact at our peril.

In the Business Intelligence field, self service is one of the most over used terms to describe the value of a BI implementation. Every vendor has a story about how their product will promote self service with your user community. Based on my experience, it is very useful to clearly categorize the types of self serve access your users can expect. This is a helpful way to segment your user base and to align your BI strategy.

Below I describe my thinking on these user segments.

Self Serve Level 1 (Report Consumer)

  • Ability to access / refresh reports on demand
  • Ability to chose pre-defined parameters to filter data
  • Ability to drill down along pre-defined paths

Basically no ability to customize reporting or explore data outside of pre-defined reports.

Technologies required: Enterprise BI Platform (i.e. MicroStrategy, Cognos, Oracle, Business Objects, etc.)

Self Serve Level 2 (Data Explorer)

  • Ability to explore exposed data sets
  • Ability to import data
  • Ability to created limited reports / dashboards

Technologies required: Data Visualization Tool (i.e. QlikView, Tableau, MicroStrategy Visual Insight)

Self Serve Level 3 (Report Author)

  • Ability to create custom dashboards and reports against any available data source

Technologies required: Enterprise BI Platform (i.e. MicroStrategy, Cognos, Oracle, Business Objects, etc.)

Self Serve Level 4 (Data Scientist)

  • Ability to load and access large volumes of unstructured, semi-structured, and structured data
  • Ability to create and test complicated models

Technologies required: Big Data (i.e. Hadoop, Other Big Data vendors), Statistical Modelling Tool (i.e. SAS, R, etc)

Note that the levels are not mutually exclusive and higher levels will have the capabilities and will leverage the technologies from lower levels.

My recommendation is to segment your user base into the above or similar segments and ensure you have the right training and tools to support each segment. Arguably you should start at Level 1 and ensure you have the basics right, but it is possible to push forward on each level in parallel, but this will drive more complexity into your BI program.

While the promise of self serve BI is real, it takes a lot of work, planning and user engagement to realize the benefits for your organization.

Image licensed under Creative Commons

Sunday, March 25, 2012

Engaging Your Users From Day 1

There is something very appealing about a report or dashboard that just speaks to you. There are lots of factors that contribute to this type of experience. For me the first thing that grabs me is the overall beauty of the layout. Is it using consistent formatting? Does the colour scheme appeal to the eye and make the visualizations easy to read? (white font headers on dark backgrounds are my favourite) Do I immediately zero in on an insight that I will take action on?

The funny thing is another person may look at the same dashboard and it doesn't say a word to them. Everyone's needs and insights are different, and we have to design our BI user experience to tailor to the end user. This is why it is so critical to engage our users at the earliest stages of the process.

My recommendation would be start with what business questions we are trying to answer, and what actions this will generate. Before the first mock-up or list of data elements is created, make sure we know what business value we are trying to deliver. Once you have determined the problem we are trying to solve, then understand what data you need to source. This is a critical step, at this point we should be working with our users on what data we need and how that data is generated. We can use this time to establish the quality of our data, and engage our business in ensuring that the data will meet our needs.

An interesting experiment at this point is to make the raw data available and allow the user to play. Let them at a cube or even an Excel pivot table, and see what insights can be pulled from the data. This will help us understand what key metrics and dashboards will speak back to the questions we are trying to answer and the actions we are going to take as a result.

If your users are engaged from day 1, you will save time and your users will be raving fans!


Saturday, February 25, 2012

BI Stands for Business Integrity

One of the key aspects of working within the field of Business Intelligence is the need for an absolute commitment to Integrity. In my career I have run across a number of situations that have put this to the test.

Data Integrity Issues

No matter the maturity of your data governance program, we have all run across situations where a data quality issue is impacting the quality of our Business Intelligence information or highlights an operational issue. Quite often these issues are highly sensitive within the organization. We have a responsibility as Business Intelligence professionals to communicate these issues to our stakeholders in a sensitive way that is focused on resolving the issue.

Truth Hurts

The facts don't lie. The beauty of Business Intelligence is that once you take a look at the data, there really is no defending the various theories that people use to operate their business in the absence of facts. Again, we need to engage our stakeholders in the process of moving to fact based decision making by having them part of the solution so they can adjust their business practices to the true reality.


Nobody is perfect. The reality is that we will make mistakes in our BI implementations by inaccurate meta data, ETL coding errors, report logic and the hundreds of other places we can make mistakes in our BI implementations. We need to raise these issues and the impact this has had to business operations and decision making. This isn't about quickly fixing and hoping no one notices, we need to be up front and accept responsibility for our mistakes.

Communicating these issues is not about sending a blanket email coldly highlighting the issues, the best way is to get out of your chair or pick up the phone and talk to people. This is not the fun part of the job. We always need to do the right thing, especially when it is hard.


Sunday, January 02, 2011

Broaden Your Horizons For those of us that have been in the BI field for a while you start thinking just about the information that is tidily organized in your data warehouse.  This can be a very limiting vision!  My biggest passion in life is connecting people with the information that can help them realize their full potential in the work they do for their organization and to develop themselves personally.  Nothing gives me a deeper sense of satisfaction like seeing someone find a new insight in their business through BI or to learn a new tool to take their leadership to the next level.

There are so many different types of information available outside of what we think of as BI data.  Here are some examples to get you thinking:

  • A leadership book that will provide some of those priceless “a ha” moments
  • The practices your organization uses to manage budgets that can help a first time manager
  • The name of the person in Operations that has a passion for Supply Chain management
  • The blog that you visit for inspiration on marketing problems

As the BI industry matures, my argument is what we typically see as BI today will become a subset of a bigger game called knowledge or information management.  As BI professionals we need to broaden our horizons to understand how knowledge and information is shared within and outside of our organizations to help connect people with what they need most.  The right information at the right time.


Monday, September 06, 2010

Book Review: Business Intelligence Success Factors

imageJust finished reading Business Intelligence Success Factors, Tools for Aligning your Business in the Global Economy by Olivia Parr Rud.  I have to admit this was a hard read and took me longer than normal to get through.

First of all, this is unlike any Business Intelligence book you have ever read.  The focus here is on how the old organizational paradigms of command control will not work in the new, connected, global economy.  In our new world, old school BI showing standard reports and dashboards to the top business leaders after a 8 month development effort simply won’t cut it.  In an increasingly quickly changing, chaotic world we need to reinvent how we approach BI in our organizations to be adaptable, resilient and connected.

The biggest “a ha” for me while reading this book was the chapter on Holocracy.  A Holocracy is the concept of having self organizing teams that are empowered to accomplish the goals of their team without a command and control structure.  We have been talking a lot in our organization about adopting Agile development practices.  In some respects we have been stuck in the mindset that this is purely for project / development teams.  What is becoming increasingly clear, is that the principles of Agile can be applied to all parts of your organization and roles.  Over the past months we have been moving in the direction of turning our team upside down and applying lean principles and empowerment of our teams across the board.  Reading about Holocracy’s in this book helped me crystallize my thinking and filled in some gaps as we move down this road.

This book covers a lot of concepts in what can feel like an unconnected way at first.  If you persevere and finish the book you will walk away with new insights and a totally different way of looking at how you implement BI in your organization.  The author provides full references to all her sources, and I would also recommend “Tribal Leadership”, “Good to Great” and “Switch, How to Change When Change is Hard.”

BI is hard, the more advanced you get in your BI capabilities, the harder it gets.  If you are a leader of a BI team you will be one of the first to feel the impact of our new world as your organization demands more and more insight to optimize your business.  It is essential that you are ahead of the curve, not on applying Business Intelligence, but on how to be a Leader in a flat, team-centered and dynamic environment.

Wednesday, August 18, 2010

TDWI Conference – Day 3 Highlights

Well, today marked the end of the BI Executive Summit at TDWI in San Diego.  It was a jam packed 2 and 1/2 days, and I got a lot of value out of the sessions.  As with any conference, not every session was outstanding, but by and large the majority of the sessions were very informative.  Here are the final highlights from the summit:

  • Semantic Intelligence is very important to understand the context of the data you have in your organization.  This is still an immature technology, but front runners will have an edge in finding hidden value in their data.
  • Look at the current tools and technologies you already have, and see how you can leverage it more.  For example, you don’t need to go out and buy predictive analytics technology out of the gate, but you can do a lot of “predictive” functionality using straight database technology.
  • Big theme of leveraging your current BI assets to provide more operational intelligence to your front lines through embedding BI information in operational systems including mobile devices.
  • The rate of change in organizations is increasing exponentially, agile approaches to deliver quicker are very critical.  Favourite quote: “You can’t predict what questions you will get tomorrow”
  • There is a lot of value in using BI to rank peers against each other to foster an environment of friendly competition.  If the sales manager in the region next to you is doing better, then there is a great opportunity to learn from them to improve your results.
  • Operational BI in action: The Virginia Police Department has decreased violent crime by 40% since they exposed operational intelligence directly to officers in their squad cars.
  • Some discussion on solid state storage to delivery blistering fast performance.  Teradata has an appliance that uses only solid state storage.  It is fast but EXPENSIVE.
  • Visualizations are very key, with increasingly large data sets and more complex business environments, only advanced visualizations can handle 1,000’s of points of data and dozens of dimensions.

Attending two sessions on predictive analytics tomorrow as I have had no exposure to this technology.  Should be interesting!


Tuesday, August 17, 2010

TDWI Conference – Day 2 Highlights

Another great day at the TDWI BI Executive Summit, covered a lot more ground today.  Here is my list of highlights and “a ha” moments:

  • Many Data Warehouses only get leveraged for standard reporting, it takes a leap to start leveraging this investment for true analytics.
  • An assessment of who does reporting / BI and what systems they leverage is an essential step to understand the requirements for BI at your organization.
  • Just having the latest tools doesn’t ensure success in your BI program, you need to engage your business closely to get true value.
  • Think hard about what will amaze and delight your end users when it comes to the customer service you provide through your BI team.
  • Text Analytics is critical to gaining insight from the vast amount of unstructured data your organization has.  Lots of great applications of how to understand and take action on the feedback from your customers.
  • Idea of having people in your BI team be adept at all parts of the technology stack from Database, ETL, and BI reporting (and requirements).  This helps ensure that you implement business logic in the right part of the stack.  For example, a report developer will put the logic in the report, because that is what they know.
  • Business Intelligence is a process of discovery, it is worthless to document requirements at the beginning of an iteration because these requirements will and should change.  Document what you have to once you have what the customer wants.
  • User happiness is the key to success, the goal of meeting the requirements as documented at the beginning of the project is meaningless.
  • Everyone on your BI team needs exposure to the end customer to truly understand their needs, including your ETL developers.  Strikes me that your ETL developers probably know your organization’s data the best, and can bring this knowledge to the conversation with your customer.
  • Lots of discussion on data governance / MDM in the afternoon:
    • Data quality needs to be part of everything you do, it is not just about a governance model
    • Idea of putting the name of the business owner on the report, they should be the ones answering questions about data quality
    • Pick your battles, only focus on data quality issues that have significant impact
    • You need to link data quality / governance to business process management, they are very tightly linked
    • It is not really about garbage data, it is about bringing together multiple, valid formats so they can be integrated and linked.

Tomorrow wraps up the BI Executive Summit with a half day of content focused on future trends in the BI space.  Should be interesting!  Stay tuned for tomorrow’s update.


TDWI Conference – Day 1 Highlights

Hippo Clip ArtIt was a long day at the TDWI BI Executive Summit yesterday, my head was spinning with everything that I heard.  Here are the highlights or “a ha” moments that I captured:

  • Lets change the term “data acquisition” to “data provisioning”.  I work for a Telecommunications company and a big part of our business is provisioning customer equipment to turn on their services.  Love the idea of us “turning on” our business partners ability to make good decisions by providing good quality data.
  • We need a “BI Review Board” that includes the front lines of our organization from the business through to IT to be involved in approving new standard reports.  This way you ensure more areas of need are met through one standard report.
  • Said it before, Agile BI requires a lot of discipline to maintain quality while delivering faster, better, cheaper.  Invest time in your enterprise data architecture as this is the baseline for everything.
  • Opening up the development of BI reports to your business is like sending a child out into the world for the first time.  You have to rely on the effort you put into developing your child (i.e. standards, best practices) to help guide them on their way (taking on their own development)
  • Avoid the HiPPO when making business decisions (Highly Paid People with Opinions).  In the absence of good data, the HiPPO rules.
  • Put more effort into asking good Questions than providing good Answers.  We need to understand the business challenge to use our data knowledge to provide information, rather than simply responding to a question.
  • How many of your BI reports are forward looking vs backward looking?  If you are reporting on what happened yesterday, your program is reactive; you need to look to the future.
  • We need to do more “A/B Testing”!  Experiment with a new idea on a small piece of your business, then analyze the results before rolling it out across the board.
  • Big theme of decentralizing your BI team to meet the needs of specific business units.  How do we do this and keep the standards and best practices that keep your Total Cost of Ownership low.
  • Unstructured data is growing exponentially faster than structured data (think social media), your BI program must take this hidden gold mine of data into account.
  • Statement: If you don’t have an analytic database capability, then your competitors do!
  • Visualization techniques are vital to understand patterns and value in large data sets.  The only way you can get 10,000 data points on one page and have it still be effective.
  • Visualization is still mostly a science, but you need that artistic ability to make it appealing and useful.  Struck me that a background in GIS will be very valuable in this space.

There of course is a lot more, but these are the ones that stuck out.  Definitely getting a ton of value out of this conference!  Highlights from Day 2 coming later this evening.  Any comments / questions, please let me know.

This is a personal weblog, and does not represent the thoughts, intentions, plans or strategies of my employer.