Bloomberg on Business Analytics
Interested in slicing, dicing, measuring, and analyzing data for customer and business insights?
According to a recent survey by Bloomberg, 97% of companies with revenues of more than $100 million are using some form of business analytics, up from 90% just two years ago.
While businesses have embraced the idea of fact-based decision-making, a steep learning curve remains. Only one in four organizations believes its use of business analytics has been “very effective” in helping to make decisions. Data is not just ignored but often discarded in many organizations as the business users can’t figure out how to extract signal from data noise.
This is a far cry from the current hype around analytics and big data, raising the questions:
- How should an organization be structured to effectively leverage analytics?
- What skillset, mindset, toolset, and governance adjustments are needed to “think outside of the box”?
- Should it be IT driven initiative or Business Unit Initiative? Enterprise BI initiatives that are too heavily IT-centric are unsustainable. BI requirements change faster than IT’s ability to keep up. Even IT organizations with the latest tools, good governance and best practices struggle to keep up with business requirements for BI applications. Unlike ERP or CRM apps, BI applications have a short lifespan and can become outdated very quickly.
That may be fine at the outset, but in order to address the larger performance improvement issues, companies need to move up the maturity curve from repeatable to defined and then to managed and optimized.
What is the focus? BI vs. Business Analytics
- focus is on retrieval and delivery of data
- monitoring and identifying exceptions
- limited variability, ambiguity, uncertainty
- reporting, dashboards, scorecards, OLAP for bounded exploration and analysis
- focus is on generation of new data, insight/foresight
- exploring data, finding insights
- expect uncertainty and probability and pattern rather than specific data
- computational and probabilistic techniques
Most firms are doing business intelligence but think they are doing analytics.
The following are research insights highlighted by the survey sample of 930 respondents:
- Business analytics is still in the “emerging stage.” While analytics has gone mainstream, most organizations still rely on traditional technology. Spreadsheets are the number-one tool used for business analytics.
- Enterprises – small, mid, large, mega — have been collecting tons of data. They are dying to get more insights from it because it’s too much of a pain to extract anything from the databases.
- Organizations are proceeding cautiously in their adoption of analytics. Use of business analytics within companies has grown over the past year, but at a moderate rate. Analytics also tend to be used narrowly within departments or business units, not integrated across the organization.
- Intuition based on business experience is still the driving factor in decision-making. Analytics is used as part of the decision process at varying levels, depending on the organization.
- Companies are looking to analytics to solve big issues, with the primary focus on money: reducing costs, improving the bottom line, and managing risks.
- Data is the number-one challenge in the adoption or use of business analytics. Companies continue to struggle with data accuracy, consistency, and even access.
- Many organizations lack the proper analytical talent. Businesses that struggle with making good use of analytics often don’t know how to apply the results.
- Culture plays a critical role in the effective use of business analytics. Companies that have built an “analytics culture” are reaping the benefits of their analytics investments.
- The real problem is changing the organization so that it more readily challenges the rationale for decisions, uses data to back up the discussion, and generates explanations.
Nothing earth shattering here….Like all innovation, adoption will take time and require significant organizational changes across toolsets, skillsets and mindsets. But make no mistake, companies that don’t embrace analytics in a fast paced competitive environment will be left behind. Take for instance Financial Services industry. The sector continues to undergo massive structural change due to de-risking, ongoing regulatory changes (e.g. Dodd-Frank act, Basel 3), curbs on leverage, competition to cash-cows like credit-cards and a massive shift to online banking. This is driving skyrocketing demand for predictive models and creating an unprecedented need for data agility.
What Is Your “Analytics Maturity ”?
In order to change, you have to baseline first – what is your analytics maturity. The business analytics maturity curve represents the arc of progression every company moves along. Maturity levels are measured by your level of experience, the implementation and support strategies you use, and your degree of sophistication around data.
Analytics maturity can be assigned to one of the following four groups:
- Reactive businesses engage in business analytics only in a reactionary mode, e.g., by complying with a customer request or in response to competitive pressure.
- Responsive companies are engaging in business analytics, but mostly as separate, one-off projects.
- Proactive organizations have established processes, infrastructure, and resources to support business analytics in a programmatic manner.
- Aggressive companies aggressively expand analytics capability as an important growth opportunity and encourage their customers to adopt it.
Which type of organization do you belong to? Where do you want to be?