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

Level Up Your Leadership Style

One of the better books about Business intelligence that I read recently was Cindi Howson’s “Successful Business Intelligence - Secrets to Making BI a Killer App”.  One chapter focusing on the organization required for a BI program referred to the concept of Level 5 leadership.  For those of you that have read “Good to Great” by Jim Collins, you are familiar with this concept, but in short Level 5 leaders are:

“Leaders who blend personal humility with intense professional will to focus not on their personal gain, but rather, on ensuring the success of the company.”

In my experience, leaders of BI organizations have a huge number of stakeholders across different areas of the business.  It constantly amazes me how many people I know across the organization due to the interactions of my role and team.  When you are in this type of situation you are constantly learning and having to rely on the individuals in the business to provide their expertise to solve their BI questions.  As a leader of a BI team you must foster an environment of collaboration and partnership across many different areas of the business.  You certainly can’t do it on your own, and you need to bring together the right people to make it happen.

Building a BI program is darn hard!  It is a long and difficult journey to move from a pre-BI environment with no tools or quality data through to a fully mature environment that provides predictive capabilities and is tightly integrated with corporate performance management.  Along the way your program will meet with many challenges and hurdles to overcome.  It takes long term commitment and a vision for the future to stick with it and make it happen.

It is essential that you have the right leadership to champion your Business Intelligence efforts.  Take stock of your own leadership abilities and those of your team before you embark on your journey.

Mark

Sometimes You Can’t Make It On Your Own

One of my favourite songs is “Sometimes You Can’t Make It On Your Own”, a signature U2-styled track.  To change the song title up a bit when thinking of BI, the title becomes “You Can Never Make It On Your Own”.  Business Intelligence is a discipline that spans many areas of IT and the business, and you need all stakeholders fully engaged in your BI program to be successful.

Due to the nature of BI architecture and applications, we are always downstream of other IT systems as they are our data source.  You must be tightly integrated with the other groups within IT managing these systems, as any changes can impact the availability and quality of your data.  For example, it is a well know fact within Data Governance programs the more you push the resolution of data quality issues back to the source systems, the more effective the solution.  BI is also a data hog, requiring large amounts of storage and processing power to analyze your organization’s data.  You need to have all the IT stakeholders invested in your BI program to ensure you have the relationships to keep your BI architecture stable.

Most importantly, BI is not an IT discipline, it is a corporate discipline.  Many BI organizations sit within IT under the accountability of the CIO, but in many other organizations this function may be centralized under Finance, Marketing or your corporate governance function.  That assumes that you are lucky enough to have a centralized BI function at all, in most organizations you will find BI scattered throughout the organization.  If we go back to the concept that this is a corporate discipline, we should be doing everything we can do encourage widespread use of common BI methodologies to maximize value.

Once you realize that you have many areas in your organization doing and supporting BI, it will become apparent that a decentralized structure is what is necessary.  To drive the maximum effectiveness you need to have some common thread pulling these groups together.  Having a competency centre type approach, where you provide common standards, access to data, and a means to collaborate are essential for success.

I will be writing a lot more about developing a competency centre to support BI over the coming months, stay tuned!

Mark

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.

Keeping your BI environment clean

Over the past year or so the "green" revolution has been sweeping IT as a way for organizations to reduce their environmental impact and to cut costs at the same time.  This has driven the need for robust measurement systems to manage the transition to being a green organization.  A number of the big BI vendors have come out with pre-packaged solutions to drive more "green"  for organizations by encapsulating best practices.

It is great for BI teams to provide these systems to the organization, but we would be remiss to not apply these techniques within our BI environments.

What can you do?  One thing I recommend you do is to perform a complete review of your Business Intelligence data stores and reporting at least once a year.  The overall goals of this review are to remove obsolete information and to address any deficiencies.  There are a number of activities you could incorporate into this review:

• Validate with your business stakeholders that the information has continuing value.  Solicit feedback on the information that is valuable, but is somehow incomplete.
• Review usage statistics for data marts and reports to determine what content is accessed regularly and by whom
• Validate that the report or data store reflects current business logic
• Gather metrics on batch load processes, response time, and storage usage to ensure your environment is stable and is scaling as volumes grow.  I've never heard of a Data Warehouse that shrinks in size over time.

The majority of these activities do not cost you a dime other than people's time.  This is especially attractive in a financial environment like today, when capital spending is being closely scrutinized.  Putting in place a regular program such as this will enable your organization to realize the following benefits:

• Reduce maintenance costs for your BI environment.  Less data marts and reports to support as your environment grows and changes.  You can quickly find yourself drowning in too many items to support.
• Lower the related data centre costs to support your infrastructure.  Believe it or not, all your ETL processes, database servers and storage solutions consume significant amounts of power and cooling.
• Identify duplicated information that is redundant.  Root out conflicting business definitions.
• Reduce the opportunity for information overload.  Having focused information will allow your users to find what they are looking for quicker.

Spare the environment and lower your costs by supporting less while extracting maximum value from your existing investments.  You can't beat this type of ROI!

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.

Keep Your KPIs Fresh

One thing that has caught my attention over the past couple of months is the emphasis on new financial metrics in this depressed market. Employment statistics used to be mentioned in passing, and now we breathlessly await the monthly numbers. Clearly the global recession is an entirely new environment, and investors would be wise to not rely on old metrics and approaches to guide them.

This made me think of how a core component of a good performance management system is keeping your metrics relevant to the current business environment they are attempting to measure. There is no such thing as permanent performance indicators. If your metrics don't change, then there is something wrong with your process. It is critical to keep your performance metrics focused on the current objectives and strategies of your business.

If your company is spending money differently, as all companies are doing in some way, then your performance indicators must change to reflect this. In these types of rapid change it is entirely possible that your core business strategy can shift significantly. It is essential that the keepers of corporate performance make it a continuous cycle to review and evaluate the suite of KPIs to ensure they are aligned to today's business reality.

This also speaks to the need for the IT organization to be able to rapidly respond to these changes in direction to provide the necessary data for the new KPIs. The best BI infrastructures are highly adaptable and responsive to change.

Step back and take a look at your metrics. Are they still relevant?

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.

Where the Business meets BI

My education and early professional career was deeply rooted in the IT world. We worried about how to keep the database running efficiently, and the best way to build a reporting portal (in the old days we built ASP pages for every single report we developed). As my career matured over the years it became apparent to me that I had to understand the business side of the equation to be truly effective. This brings to mind one of the challenges we all face as leaders of Business Intelligence initiatives, where can we find the right people?

We have the distinct need within Business Intelligence to fully understand what problem the business is trying to solve, and then to understand what data is available to solve the problem. I've heard many great ideas from the business that would add a lot of value to the organization, but the data is simply not available or is of questionable quality. This is where the role of the Business Intelligence Analyst comes into play. For the purposes of this post, the BI Analyst is the person that gathers requirements from the business and then works with the IT teams to deliver the information. (I've seen about 6 different roles described when talking about a Analyst role on a BI team).

A black belt BI Analyst has 2 distinct areas of expertise:

1. Business knowledge - Deep understanding of the business processes and models is necessary to properly "interpret" what the users are looking for.
2. Data knowledge - An understanding of not only the data structures that are available, but how the business processes interact with the source systems which eventually filter into the data we have available to BI.

This blend of skills and expertise requires a very specific type of person. If I was to describe the qualities of a BI Analyst, the following comes to mind:

• Hyper-analytical - Able to apply critical thinking skills to get to the heart of the problem
• Diplomatic - Being able to guide the business in the right direction without telling them their idea won't work...8)
• Passionate - To truly get to the heart of a problem requires tenancity and buy-in to the organization's goals

The BI Analyst is a critical component of any BI initiative regardless where in the organization this role sits. Without the proper attention to requirements and desired outcomes, a project as complicated as a typical BI initiative is very likely to fail or to fall short of our client's expectations. One of the best sources for a BI Analyst, is within the business units we serve. You likely have someone working in the business that has the right type of analytical mind set to be a "black belt"!

Mark

Ensuring BI Projects don't Fail

Presentation from Timo Elliott, Business Objects.  Great slides!

Why Business Intelligence Projects Fail -- And What To Do About It

Mark

Don't Let Budgets Hold You Back

Just read an article from the Data Warehousing Institute on how to move forward with data warehousing / business intelligence initiatives when you have limited funding and resources available to you.  The idea is to use these techniques to provide visible business wins that should translate into additional funding being available for your BI program.

This is actually a 3 part article that looks at the problem from 3 perspectives (click to see article):

• Technology & Tools - How to leverage what you already have / expanding on existing vendor relationships.
• People - The typical roles required on a data warehousing project and how to combine them
• Project Selection - Steer around projects that require significant resources and have high complexity, instead go for the quick wins or low hanging fruits.

Good read for anyone in the field, we don't need a 10 pound sledgehammer to nail a picture to the wall!

Mark

BI's Place in the IT Portfolio

Good morning, ran across an interesting article on where Business Intelligence fits within an overall IT portfolio.  The below is an interesting picture of this:

Nice to see this on top of the chain isn't it?  8)  Here is the link:

http://www.b-eye-network.com/view/index.php?cid=7498

Dealing with Culture

How does the culture of the organization impact the adoption of Business Intelligence?

This is a great question we need to ask ourselves as we move the vision of Business Intelligence forward in our organizations. Depending on the organization, your BI program will be successful based on how the program aligns to the culture of the company.

For example, lets envision a culture where finding cost efficiencies is a core mission of the organization. Think of some type of commoditites industry where margins are razor sharp, and every .001% improvement can be what makes or breaks the organization's profitability that year.

In this type of pragmatic organization, you would entirely miss the boat if you came in with a solution that provides demographics on their customer base and opens up new opportunities for them. In this type of culture, they may not be looking for new opportunites. We just want to procure it, process it and sell it on the open market! Beware those BI practitioners that stray from a services industry...8)

This is a pretty crude way to point out that you need to know your organization and it's culture to understand how to position your BI strategy. Tailor your approach using vocabulary and outcomes that align with organizational culture and you will be saying the right things to be successful.

Have a good night!

Mark