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

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.

Mark

Book Review: Business Intelligence Success Factors

Just 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.

BI Leadership Article

It isn’t often you come across a good article that brings together developing a Business Intelligence vision and the behaviours BI leaders need to demonstrate to make this vision a reality.  Well worth a read if you are a BI leader or are just trying to understand them…8)

Creating Shared Responsibility for Success in Your Business Intelligence Team

I’m glad to see we are already doing some of this in my current organization, but there are a number of areas discussed in this article that can be improved.  The fun never ends!

P.S. Apologies for the lack of updates to this blog, good weather calls!

The Tactical Data Mart Advantage

The capabilities of current BI tools allow us to drive down the costs to develop BI applications / data marts.  This means that we can quickly develop tactical applications leveraging standard tools and methodologies to reduce development cycles.  This enables the deployment of applications to support specific decision making problems that would normally not be supported by a quality BI environment due to the short turnaround required.

Some people get upset about building these so called silos that aren't integrated.  I take a different perspective that these tactical data marts expose the power of tactical Business Intelligence, and if you manage it well they are a great complement to your core infrastructure.

"A good solution applied with vigour now is better than a perfect solution applied ten minutes later.” - General George S. Patton

It is critical that you have a checkpoint or a regular environment review that you can rely on to take one of the following actions at the end of the decision making life cycle:

1. Decision has been made and there is no need for continued access to the data mart.  Simple response, retire the data mart and free up system resources for the next initiative.  Celebrate the success.
2. The information within the data mart has continuing value to the organization.  In this case you need to have room in your requirements funnel to incorporate the data mart into your permanent BI infrastructure.

Don't hold your business back by sticking to a traditional release cycle.  Build a team within your BI program that can quickly spin up the appropriate BI solution to support tactical decision making.  You can't win the war if you don't win a battle now and then!

Data Integration and Your Organization

Today we had John Schmidt, VP of Global Integration Services at Informatica come speak to our teams about best practices for setting up an Integration Competency Centre (ICC).  John made an interesting point that your various Integration functions may be included in Competency Centres in different ways depending on the organization.  

If you have researched Business Intelligence Competency Centres (BICC) you will often find a Data Integration function as one of the functions staffed within the BICC.  However, Business Intelligence is just one part of the pie when it comes to integrating information across the enterprise.  You will also need data integration expertise for data quality, Master Data Management, and other non-BI specific projects.  A number of these projects may not impact BI significantly if at all.  If you want a holistic view of data across your organization you must either create a standalone ICC with strong ties to your BICC, or incorporate all areas of integration practice within a higher level Information Management Competency Centre.

Good BI is enabled by quality data.  Since data quality lives along the information management timeline from your source systems to your analytic databases, it is critical you have technology, process and people engaged all the way along to ensure the best data is delivered for BI.

CIA: Collaboration in Action

One of the greatest examples of effective collaboration is the partnership between 007 and Q in the James Bond movies.  Q would design and build gadgets that seemed to be uniquely suited to the next round of challenges and daring escapes James would encounter on his upcoming mission.  During each movie it appears that James just drops in to Q's lab after receiving his assignment to find everything he needs ready and waiting for him.

Being this ready for anything doesn't happen magically, but is the result of an agile development methodology.  Delivering information solutions is a constantly changing landscape that can benefit from applying the design principles used in Q's lab.

• Rapid Prototyping - Every time James would drop by, the "latest" version of a new tool is ready to be tried.  Take every opportunity to show your users the look and feel of your solution, this will unleash their creativity and you will benefit from their increased engagement and suggestions.
• Fail and Fail Fast - These gadgets would often have unintended side effects, or would explode spectacularly.  There was never any other reaction than cool, collected analysis to fix the problem.  Create an atmosphere where the ability to quickly fail, learn from the mistake, and try again happens as quickly as possible.
• Open Environments - Tests were not undertaken in closed laboratories, but were instead conducted in environments that were open to other researchers and their devilishly handsome customers.  Have a physical environment that encourages collaboration with everyone that is core to a project.  Virtual environments are great, but nothing replaces in person communication.
• Continuous Improvement - Every time 007 returns his shot up, smoking, destroyed vehicles, he provides feedback directly to the designer on what did and didn't work properly.  Find different channels to receive feedback from your users, and make a point of acting on it.

Business Intelligence is not something that is done well in isolation.  Encourage your team to use the above concepts, and look for every opportunity to engage the right people in your initiatives no matter what area of the organization they are from.

"Now do please remember to take care of all this equipment 007...DON'T TOUCH THAT!!...That's my lunch!" - Q

BI for BI

One of the core disciplines within a Business Intelligence team or program is to develop internal metrics and performance management practices. The idea of "BI for BI" is to exploit your internal strengths and live the fact-based decision mantra.

Business Intelligence is a core component of corporate performance management systems. Conversely, Business Intelligence can only deliver maximum value when it is coupled by a strong performance management culture. In order to communicate the value of spend on BI / performance management initiatives, we need to talk about both the BI technology and the culture required to support it.

If we have the management practices in place to constantly act on and refine our internal program / departmental metrics, we can then use this as a working example to the rest of the organization. Not only will you be able to demo the metrics produced for your team, but you will be able to relate success stories that you had acting on this information. Not only show a dashboard trending average bugs per release, but also tell the story of how your team saw a negative trend 6 months ago, implemented an improvement to the code review process, and reduced overall bugs by 50%. How powerful is that!

Here are just a couple examples of metrics you could put in place to measure your BI program:

• ETL Job Completion Times
• Uptime by Infrastructure Component (Presentation, ETL, Database Layers)
• Volume of Requests for Information
• Average Frequency of Visits to BI Portal (i.e. 3.5 times per week)
• Volume of Data Quality Issues
• Resolution Time on Service Tickets
• Production Incidents by Severity
• Changes to Report / Asset Catalogue

A couple hints on how to put this in place:

• Make people accountable for their metrics. They own them and report on them.
• Start small and grow. Start with measuring only a handful of metrics, and add additional metrics over time. Look for patterns of key performance indicators, and their relation to other metrics.
• Review and publish your metrics. Have a regular time set for metric review. Make metrics available to anyone that interacts with you, including your customers. Open the Kimono!

It is a basic professional requirement for an organization to produce regular metrics on their performance. Leverage your team's expertise in the discipline of Business Intelligence to improve your team's performance, and show the rest of the organization how it is done!

The Agile Organization: Powered by Data

One of the core characteristics of an analytical competitor is the ability to rapidly leverage the organization's data to make decisions faster than their competitors. Being first to market with a new idea, product or service will ensure success when the profit margins are high before the big new thing becomes a commodity.

Here is an example of a business using analytics to gain market share:

We need to retain our high end customers with a loyalty program. Who are our most profitable customers?

Our most profitable customers must be the ones that drive highest revenues, lets go and see what this customer base looks like.

Thus begins a cycle of analysis to answer this question.

• Data Discovery - What data is available on revenue? What systems contain this data? What is the quality and integrity of the data?
• Data Acquisition - Know that I know what data is available, how do we get it? Does it have to be brought into the Data Warehouse? Do I need to get an extract from the ERP system?
• Analysis - Looks like our highest revenue customers are large call centres...
• Act - Call these clients as the pilot group to offer them 5% off new equipment installs.
• Measure - Gather feedback from commercial account reps

Feedback comes in stating that many customers offered this discount said they would prefer more free support calls instead. What type of support call volume do we have anyway?

So begins another cycle of analysis to look at support call volume. If this data does not exist in a readily available source such as a Data Warehouse, then we have to go through the whole cycle starting with Data Discovery.

If we go through this again, we will likely lose at least days if not weeks until we are able to determine the next course of action on our journey to retain our most valuable customers. If a company is able to cut out the Data Discovery and Data Acquisition phases, they will be that much farther ahead of the competition.

Having high quality data that is available to decisions makers when they need it is essential to becoming an analytical competitor. Focus on building out a robust information architecture that contains data that is relevant to your business today. With this approach you will literally be two steps ahead of the competition.

For What It's Worth - My 2009 Predictions

I recognize that I am a little behind the ball on predictions for the BI space in 2009.  We are technically not a full month into the new year, so I'll sneak this in.  I have to admit that I have had the opportunity to read a number of other posts on this topic, so I have late bloomer advantage.  I'll focus on areas that I think will have a large impact on us all.

Drum roll...  2009 BI Predictions

• The Big 4 (SAP, IBM, Microsoft, Oracle) will continue to gain market share in the Business Intelligence and Performance Management spaces.  This will be driven by the ongoing consolidation and integration of the various home grown and acquired technologies to deliver a more cohesive user experience.  These platforms will be attractive to the IT organization due to the ability to consolidate licensing with one vendor and to have one set of management tools to support.
• Open Source BI platforms will spread BI below the $500M in revenue organization.  The cost of mainstream BI platforms can be prohibitive for small to medium size companies.  Open Source platforms will open up the power of BI to these organizations, allowing for zero cost proof of concepts and a lower TCO for a supported enterprise solution.  Expect these platforms to deliver 80% of the functionality at 20% of the cost.
• Business Intelligence becomes a core requirement.  Given the uncertainties in the market, we will see an increased awareness of the importance to have the information to make the right decision.  In a strong market where people are buying products and services, it is easy to roll with the times and accept positive results without really knowing why.  When times get tough, risk tolerance becomes much lower.  This risk is mitigated by having the best possible information to make the decision at hand.

No matter what, it should be an exciting year!

For an exhaustive list of BI predictions for this year, visit the BI Questions Blog for a consolidated list.

BI Questions Blog - The Complete List of 2009 BI Predictions?

Leapfrogging the Competition

These are unsettling times, every family and every organization is looking closely at what they spend their money on, and the value they get from these expenses.  In order to do this effectively, it all comes down to making sound decisions with the best possible information you can obtain.  You wouldn't decide to change anything in your household, such as trading in your SUV for a Volkswagen without understanding all the angles such as financing, gas mileage, capacity, warranty, etc.  Hmmm, decisions and information... sounds like a recipe for Business Intelligence!

Every organization is in their own unique way poised to take advantage of better access to information to make sound, informed decisions to guide them in this current market economy.  Rather than cutting costs without understanding the long term impacts, use information and analytics to truly understand the cost from all angles (slice & dice).  We can also use information to look for new opportunities, such as using this downturn to acquire customers from our competitors by targeting them with advertisements that show the value of the product to them (segmentation & personalization).

This may be the time to consider increasing your company's investments in Business Intelligence technology and people, rather than trimming costs.  ROI doesn't stop happening in a down market, get out there and leapfrog your competition!

Balancing your BI Strategy

For those of you that lead Business Intelligence teams or programs, you likely have encountered a big dilemma...  How can we move forward with a Business Intelligence strategy when there is such a big demand for information today?  In most organizations the demand for information far outstrips the resources available.  Information providers in an organization are consumed with resolving repeatable data quality issues, delivering endless cuts of information, and then delivering it again next month.

If we added up all the resources and time taken to keep pace with this flow, we would quickly see a lot of money being spent without delivering a lot of sustainable value.  I've seen this struggle manifest itself a number of times, and have found that it is possible to do both.  Not easy to balance, but possible.  There are 3 areas of focus that enable this:

• Sell Business Value
• Separate Resources
• Deliver Incrementally

Sell Business Value

Due to the nature of Business Intelligence solutions, it is important to communicate the value of investing in long-term, sustainable solutions.  These business benefits can include a quicker turnaround on requests, more self service information, and higher data quality.  Find the benefits that fit your organization, and communicate to your key stakeholders.  You need to show what value you can deliver to their organization, and to the bottom line.

Separate Resources

As you communicate the value of strategic BI solutions to your stakeholders, also identify the need to dedicate resources to building these solutions.  Align on the number of resources that will be dedicated to building strategic solutions vs. resources dedicated to tactical response.  It is important to identify the impact of these decisions to the operational capacity that will now be available.

As you focus resources on building strategic solutions, ensure that communication tools and knowledge sharing exist between both sides of the organization, strategic and tactical.  Resources supporting tactical requirements have comprehensive knowledge of information requirements and can be a big asset in driving user adoption of the new solutions.

Deliver Incrementally

To quickly prove the value of this approach, you must deliver incremental solutions that deliver direct value to the organization.  Delivering using an agile approach will allow you to maintain your momentum and build a community around using BI tools.  Having architecture talent and good design processes will ensure that the incremental solutions build into a larger, enterprise view.

As part of your BI program or competency centre, communication and engagement with your user community is vital to deliver solutions that provide the maximum amount of value.  Finding a balance between operational support and strategic delivery will help you achieve the goals of your BI program.

How can BI get agile?

We are hearing a lot about how Agile software development techniques deliver more value quicker to the end user. The market and competition is changing faster every day, software development must be able to change with it. In our world today, we can't afford to wait for results from a traditional waterfall approach, when what we deliver will not meet current requirements.

Anyone that has been exposed to agile methodologies sees why this is such a powerful approach. I have to ask myself... Why don't we see more BI projects leveraging agile? Agile has been more prevalent and quickly adopted in the SOA / App / User Interface areas than in the data side of the world.

If we think back on the history of BI projects, we are not too far from the time when we had a failure rate of 50%! Why did they fail? Long duration, high complexity, high cost, and not delivering what the business needed, when they needed it. Sounds like a recipe for Agile to me!

I challenge you to shake off the dust and find how you can deliver in new and innovative ways. The excuse that "We don't have that data in the warehouse" is simply not acceptable in today's world. We need to be able to gather requirements, profile data, data model, build ETL routines, build reports / dashboards / visualizations, and deploy to production in the space of 2 weeks. Or why not 1 week?

Here is some reading:

Agile Data - DW Best Practices

Agile Manifesto

Follow up article to it Just Has to Work

I was catching up on my reading, and ran across the below article that had a similar view as my post on "It Just Has to Work".  Tom Hudock at Business Intelligence for Business People has a great post about a similar concept.

Now imagine what BI would be like if you could simply stitch your information together? Pull your customers. Drag sales volumes. Drop products into an information pot. Then BI does the rest. You then navigate the answers. Repeat with new information when ever you need to.

http://biforbusinesspeople.blogspot.com/2008/08/stitch-your-information-together.html

The Next Step in a BI Vision

In my post on Creating a Positive Future, I discussed the importance of understanding Business Intelligence requirements from the perspective of your end users.  Once you understand the user experience you need to provide, you are able to ensure that your delivery on this vision meets expectations.

Ok, so now you know what your users are looking for.  Great!  Let's jump in and start building the solution!

Not so fast...  We need to prepare the organization for this massive shift towards an intelligent, fact-based decision making organization.

In a number of my earlier posts I have discussed the Business Intelligence Competency Centre (BICC) as a key component to ensure Business Intelligence projects and resources are aligned to business priorities.  As we spread our wings with Business Intelligence tools it is absolutely critical that we have the underlying processes in place to support both the developers and users of the technology.  Without the appropriate organizational and process support we will not be successful realizing the benefits of Business Intelligence.

There are a number of books available that provide a good overview of a BICC.  One that I have found useful is the "Business Intelligence Competency Center: A Team Approach to Maximizing Competitive Advantage" written by a group of SAS staffers.  It is written vendor neutral, with just a little marketing pitch...8)  I would also encourage you to reach out to your Business Intelligence platform vendors and solution partners, as they will likely have experience launching a competency centre and may have their own methodologies you can borrow from.  It can be invaluable to have a neutral 3rd party help you with this process, so that you can leverage their experience.  That is if you can afford it!

Stay tuned for more thoughts about the BICC over the next couple of months.

I Dream of Data

For those of you that aren't certified "data geeks", you would probably not understand dreaming of data.  For some of us this love affair is new, and for some of us this has been a long standing obsession.

I clearly remember the first time I got the data bug.  It was an entry level database programming course and the lab assignment was to build and execute SQL scripts (inserts, deletes, updates, selects) against a provided data model using an Oracle (v5 I think) database.  It just seemed so natural to examine the data model and the problem and just pick what you wanted and join tables to build "grids" of data.  The career path in IT was set from the 2nd year in university!

Throughout my career, I have always been fascinated by manipulating data to gain insight into what is happening in the business of my organizations.  This has fostered a deep appreciation for the value of Business Intelligence, but on a larger scale an appreciation for how overall data management is critical to the success of an organization.  The Business Intelligence discipline must be supported by other components of an Enterprise Information Management (EIM) strategy such as Master Data Management (MDM), Data Governance, Data Architecture, and Data Quality Management to provide maximum value to an organization.  To forge ahead without engaging the rest of your IT department in treating data as an asset is a recipe for frustrated teams and ineffective solutions.

So when I fall asleep, I dream of a perfect environment where all pieces of an Enterprise Information Management strategy are in place.  Sometimes I feel like I am drawn to a big light at the end of a long corridor filled with data.  When I finally get to the end I see beautiful visualizations of information presented by my local Business Intelligence portal, harnessing all the inherent value in my beautifully managed data sources.  This is a big dream, but what dream worth pursuing is easy?

Good night, sleep tight!

Creating a Positive Future

If you have spent any time on the Internet researching a topic like Business Intelligence / Knowledge Management, it can be very overwhelming when you consider all the pieces that need to be implemented to have your organization on the leading edge in this field.  This is not just a technology evolution, you also must consider the people and process components to implement a successful Business Intelligence program.  Especially in today's business world, an organization has to find a balance between keeping the current operations running to respond to the latest market opportunity, and building strategic capabilities to support the future and provide competitive advantage.

This is a daunting task, so where to begin?  If you have done any reading on the power of positive thinking you may have run across references to "Creating a Positive Future".  The idea is that if you can en-vision what you would like things look like in the future, then you can work backwards to get there.  Think of it as a top-down rather than a bottom-up approach.

Your first step is to approach this from the experience you want your clients to have.  You must start by talking to your users to understand what business pain points you can solve for them.  Now if you are in a situation where they don't currently have a lot of BI capabilities, you will likely here a lot about what you are not providing now.  That is ok, you need to understand these pain points to ensure you cover them off in your future state.  In an organization more mature in leveraging information, you will hopefully hear about some great new opportunities that BI technology can help with.

Start by working from a what is possible perspective.  Don't burden yourself with the current limitations of people, funding or technology as this will in turn limit your vision.  Build a vision based on your experiences, research on what other companies are doing, but most importantly spend time with your clients to ensure you fully understand what they are looking for.

If you focus on what is possible, instead of what you aren't doing today you can build a positive future for the implementation of BI in your organization.  Watch out for future posts on the next steps to develop your BI roadmap once you have this vision.

P.S.  This is my first post using Windows Live Writer to post to Blogger.com.  Works great!  A big thank you to my colleague Frank Vandongen for suggesting it.