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Business Intelligence Innovation Summit 2014 Chicago: Day 1 Highlights


Highlights from the presentations by Business Intelligence leaders from Boeing, Salesforce, Wells Fargo, and Citibank on day 1 of Business Intelligence Innovation Summit 2014 in Chicago.



Business Intelligence (BI) is playing a key role in modern business and is considered central to identifying new opportunities within an organization. Making use of new opportunities and implementing an effective strategy can provide a competitive market advantage and long-term stability for a business. Using Business Intelligence theories, methodologies, processes & more is paramount to the success of such pursuits.

The Business Intelligence 2014 Chicago Business Intelligence Innovation Summit (May 21 & 22, 2014) organized by the Innovation Enterprise at Chicago, IL covered major challenges and opportunities being observed by BI leaders across industries. The summit featured an industry led speaker line-up consisting of 25+ leading business analysts, data scientists, intelligence developers, business researchers and business intelligence leaders.  BI leaders shared their perspective on common challenges, best practices and real-life case studies.

We provide here a summary of selected talks along with the key takeaways.

Here are highlights from Day 1 (Wednesday, May 21, 2014):

Harish RaoHarish Rao, Director, Business Analytics, Boeing delivered an insightful talk on "Insight-Driven Approach as a Competitive Advantage". Information management plays a significant role in promoting an insight-driven culture. Areas like data quality, metadata, data lineage and master data must be addressed to ensure successful and systematic decision-making across the enterprise. He explained why approaching Analytics process as a discipline, as opposed to a project–based approach, can further organizational success.

He listed the pre-requisites for analytical success as: well understood problem, good quality data, choice of tools and skilled analysts. The high level benefits of Analytics are revenue generation, cost containment and process improvement. The Analytics process boosts revenue generation through:
  • Validating revenue generating hypothesis (sandbox & prototype)
  • Developing decision alternatives (modeling & controlled pilot)
  • Effecting change (measure & deliver results)

 
Business Analytics and Information Management should always focus on business adoption, improved speed to market, data quality, and innovation. He also explained how these concepts can best be applied to achieve real business results.

Gary SarkesianGary Sarkesian, Vice President, Customers For Life, Salesforce described the importance and key characteristics of Open Innovation in his talk titled "To be a Disruptor or to be Disrupted?". 96% of all innovations fail, with some of the most common innovation challenges being fragmented conversations, too many platforms and lack of unified approach. As defined by Prof. Henry Chesbrough, Open Innovation is the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively. The central idea behind Open Innovation is that in a world of widely distributed knowledge, companies cannot afford to rely entirely on their own capabilities or create new capabilities. In contrast to Closed Innovation, Open Innovation is based on the premise that External R&D can create significant value; Internal R&D is needed to claim some portion of that value.

He explained the various steps involved in the ideation workshops, which synthesizes the best elements of business process, trends, human collaboration, hindsight, business intelligence and broad opportunity insight to connect customers, employees, and partners into an Open Innovation strategic blueprint to become a Disruptor. Next, he gave examples of how companies such as GE, General Mills, and Philips are following the Open Innovation approach for market leadership. In summary, he mentioned that Open Innovation Model is the future - through Open Innovation model organizations keep strong relationships with external parties at different stages of the innovation development process.

Darren LovinDarren Lovin, Manager, Business Intelligence, Wells Fargo shared his experience of managing the talent challenge, in his talk "Growing a BI Practice from Within". A constant challenge in staffing a BI team is acquiring talent that has both the technical know-how and the business acumen needed to excel in a consultative BI role.  Retention and continuity are also of high importance in order to service the business teams. The major challenges in front of Wells Fargo BI team were poor data environment, antiquated software and inadequate staffing. The vision to overcome these challenges focused on self-service, consultative, and predictive capabilities. It is particularly hard to find good talent for BI because of the niche toolsets involved, required passion and strong soft skills.

In July 2013, Wells Fargo created the Experiential Learning Program.  The program allows internal team members, who express interest and pass minimal qualifications, the opportunity to ‘intern’ with the team.  As an ‘intern’, they learn technical skills such as SQL, and Cognos report writing as well as basic database knowledge.  The intention of this program is to achieve a win/win outcome for both the BI team and the intern.  The win for the intern is the opportunity to learn a set of skills and gain first hand insight into a new career path.  The win on the BI side is, if the intern excels at the technical aspects of the job, this coupled with the intrinsic knowledge of the business they should already possess, they become a strong candidate to fill any upcoming staffing needs on the team.

Vinay GandhiVinay Gandhi, Vice President, Business Intelligence & Communications, Citibank gave an interesting talk on "Business Intelligence & Communications". He started his talk with a very interesting quote: "Data is growing at the fastest pace it ever has and at the slowest pace it ever will". Next, he talked about different layers of data processing including data transformation (ETL), connectivity, reporting, analysis, performance monitoring and prediction. Given the complexity of technology and variety of options, picking the right vendors can be difficult.

He ended his talk describing the importance and process of getting meaningful analytics delivered in a visual message at the right time, using the following three key aspects of business intelligence:
  • Analytics- Importance of creating accurate and actionable metrics
  • Visualization- Depicting analytics in a method that is easy to digest, adds value, and leads to action
  • Cadence- Delivering the message at the right time and in the right methodology

 
Highlights from Day 2.

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