business intelligence

 

Every self-respecting data management professional knows that “business alignment” is critical to the success of a data and analytics program. But what does business alignment really mean? How do you know if your program is aligned to the business?

Before describing what business alignment is, let me first list what it is not:
• Interviewing end users to understand their needs for data and analytics
• Recruiting a highly placed and influential executive sponsor
• Documenting a high return on investment
• Gaining agreement on the data strategy from multiple business areas
• Establishing a business-led data governance program
• Establishing a process to prioritize data requests and issues

It’s not that the items on this list are bad ideas. It’s just that they are missing a key ingredient that, in my experience with dozens of clients, makes all the difference. None of these items are even the best first step in developing a data strategy.

So what’s wrong with the list? Let me illustrate with an example. I was working with a team developing a data strategy for a large manufacturing company. We were interviewing a couple of high level managers in marketing, and it went something like this:

Me: What are some of the major business initiatives that you’re expected to deliver this year and next year? Do you have some thoughts on the data and analytics that will be needed within those initiatives?

Marketing manager: Sure, well, we have this targeted marketing initiative that we think will be a big winner. When a customer contacts us for warranty information, we think we can cross-sell products from another business unit… here’s a spreadsheet… we’ve calculated that this will bring back $14 million in additional revenue every year. We’re so excited that you’re doing the data warehouse initiative… We’ve been proposing this marketing idea for the last four years and haven’t been able to get it approved, and now we can finally get it done!

Me: I didn’t ask what you think the business initiatives should be; I asked you what they already are! (Ok, I really didn’t say it that way, but I wanted to.)

Why couldn’t they get the project approved? Who knows? Maybe the ROI was questionable. Maybe the idea wasn’t consistent with the company strategy and image. All that matters is that it was not approved, and hence makes for a lousy value proposition for a data and analytics program.

There is nothing wrong with proposing exciting, new “art of the possible” ways that data can bring value to the business. But an interesting proposal and an approved initiative are not the same thing. The difference is crucial, and data management leaders who don’t understand this difference are unlikely to be seen as trusted strategic advisors within their companies.

So what does it mean to be business aligned? Business alignment means being able to clearly state how deployment of data, analytics, and data management capabilities will directly support planned and approved (meaning funded) business initiatives.

So, the first step toward developing a successful data strategy is not to ask the end users what data they want. Instead, the first step is to simply find the top business initiatives. They are usually not hard to find. Very often, there are posters all over the place about these initiatives. There are a number of people in the organization you can check with to find top initiatives - the CIO, PMO leads, IT business liaisons, and contacts in the strategic planning department are examples of good places to start.

Then, you should examine the initiatives and determine the data and analytics that will be needed to make each initiative successful, especially looking for the same data needed by multiple projects across multiple initiatives. Core, enterprise data is usually needed by a diverse set of initiatives in slightly different form. For example, let’s say you work for a retailer and you identify approved projects for pricing optimization, labor planning, and marketing attribution. You can make a case that you will deploy the sales and product data these applications need, in the condition needed, in the time frame needed.

Proceeding further, you can propose and champion a series of projects that deliver the data needed by various initiatives. By doing this, along with establishing architecture and design principles of scalability and extensibility, you harness the energy of high-priority projects (instead of running away from it) to make your business case, add value by supporting the value of pre-vetted initiatives, and also build a foundation of integrated and trusted data step by step, project by project. Once this plan is established and in motion, you can accurately state that your program is absolutely needed by the business and you are also deploying data the right way – and you can also say that your program is officially business aligned.

Guest Blogger Kevin Lewis is responsible for Teradata’s Strategy and Governance practice. Prior to joining Teradata in 2007, he was responsible for initiating and leading enterprise data management at Publix Super Markets. Since joining Teradata, he has advised dozens of clients in all major industries.

Change and “Ah-Ha Moments”

Posted on: March 31st, 2014 by Ray Wilson No Comments

 

This is the first in a series of articles discussing the inherent nature of change and some useful suggestions for helping operationalize those “ah-ha moments."

Nobody has ever said that change is easy. It is a journey full of obstacles. But those obstacles are not impenetrable and with the right planning and communication, many of these obstacles can be cleared away making a more defined path for change to follow.   

So why is it that we often see failures that could have been avoided if changes that are obvious were not addressed before the problem occurred? The data was analyzed and yet nobody acted on these insights. Why does the organization fail to what I call operationalize the ah-ha moment? Was it a conscious decision? 

From the outside looking in it is easy to criticize organizations for not implementing obvious changes. But from the inside, there are many issues that cripple the efforts of change, and it usually boils down to time, people, process, technology or financial challenges.  

Companies make significant investments in business intelligence capabilities because they realize that hidden within the vast amounts of information they generate on a daily basis, there are jewels to be found that can provide valuable insights for the entire organization. For example, with today's analytic platforms business analysts in the marketing department have access to sophisticated tools that can mine information and uncover reasons for the high rate of churn occurring in their customer base. They might do this by analyzing all interactions and conversations taking place across the enterprise and the channels where customers engage the company. Using this data analysts then begin to  see various paths and patterns emerging from these interactions that ultimately lead to customer churn.   

These analysts have just discovered the leading causes of churn within their organization and are at the apex of the ah-ha moment. They now have the insights to stop the mass exodus of valuable customers and positively impact the bottom line. It’s obvious these insights would be acted upon and operationalized immediately, but that may not be the case. Perhaps the recently discovered patterns leading to customer churn touch so many internal systems, processes and organizations that getting organizational buy in to the necessary changes is mired down in a endless series of internal meetings.   

So what can be done given these realities? Here’s a quick list of tips that will help you enable change in your organization:

  • Someone needs to own the change and then lead rather than letting change lead him or her.
  • Make sure the reasons for change are well documented including measurable impacts and benefits for the organization.
  • When building a change management plan, identify the obstacles in the organization and make sure to build a mitigation plan for each.
    Communicate the needed changes through several channels.
  • Be clear when communicating change. Rumors can quickly derail or stall well thought out and planned change efforts.
  • When implementing changes make sure that the change is ready to be implemented and is fully tested.
  • Communicate the impact of the changes that have been deployed.  
  • Have enthusiastic people on the team and train them to be agents of change.
  • Establish credibility by building a proven track record that will give management the confidence that the team has the skills, creativity and discipline to implement these complex changes. 

Once implemented monitor the changes closely and anticipate that some changes will require further refinement. Remember that operationalizing the ah-ha moment is a journey.  A journey that can bring many valuable and rewarding benefits along the way. 

So, what’s your experience with operationalizing your "ah-ha moment"?

Big Apple Hosts the Final Big Analytics Roadshow of the Year

Posted on: November 26th, 2013 by Teradata Aster No Comments

 

Speaking of ending things on a high note, New York City on December 6th will play host to the final event in the Big Analytics 2013 Roadshow series. Big Analytics 2013 New York is taking place at the Sheraton New York Hotel and Towers in the heart of Midtown on bustling 7th Avenue.

As we reflect on the illustrious journey of the Big Analytics 2013 Roadshow, kicking off in San Francisco, this year the Roadshow traveled through major international destinations including Atlanta, Dallas, Beijing, Tokyo, London and finally culminating at the Big Apple – it truly capsulated the appetite today for collecting, processing, understanding and analyzing data.

Big Analytics Atlanta 2013 photo

Big Analytics Roadshow 2013 stops in Atlanta

Drawing business & technical audiences across the globe, the roadshow afforded the attendees an opportunity to learn more about the convergence of technologies and methods like data science, digital marketing, data warehousing, Hadoop, and discovery platforms. Going beyond the “big data” hype, the event offered learning opportunities on how technologies and ideas combine to drive real business innovation. Our unyielding focus on results from data is truly what made the events so successful.

Continuing on with the rich lineage of delivering quality Big Data information, the New York event promises to pack tremendous amount of Big Data learning & education. The keynotes for the event include such industry luminaries as Dan Vesset, Program VP of Business Analytics at IDC, Tasso Argyros, Senior VP of Big Data at Teradata & Peter Lee, Senior VP of Tibco Software.

Photo of the Teradata Aster team in Dallas

Teradata team at the Dallas Big Analytics Roadshow


The keynotes will be followed by three tracks around Big Data Architecture, Data Science & Discovery & Data Driven Marketing. Each of these tracks will feature industry luminaries like Richard Winter of WinterCorp, John O’Brien of Radiant Advisors & John Lovett of Web Analytics Demystified. They will be joined by vendor presentations from Shaun Connolly of Hortonworks, Todd Talkington of Tableau & Brian Dirking of Alteryx.

As with every Big Analytics event, it presents an exciting opportunity to hear first hand from leading organizations like Comcast, Gilt Groupe & Meredith Corporation on how they are using Big Data Analytics & Discovery to deliver tremendous business value.

In summary, the event promises to be nothing less than the Oscars of Big Data and will bring together the who’s who of the Big Data industry. So, mark your calendars, pack your bags and get ready to attend the biggest Big Data event of the year.