- log in
Posted by James Staten on August 26, 2013
There is a reason the phrase, “beauty is in the eye of the beholder,” has held significance and power in our society for so many generations. And in that phrase is a lesson for all of us about business analysis. The power of different points of view examining a given set of inputs is key to truly understanding what lies before us and seeing the new possibilities and different threats looming.
Sit silently in a museum listening to the patrons take in just a single painting and within a day you will hear a hundred different insights, many of which you didn’t see before. Insights that show you things in that artwork you never would have seen, such as the way greens and reds are mixed to create hues that don’t invoke their origins, the style of brushstrokes used that convey depth and how a pattern viewed up close can be very different than the whole. So much insight doesn’t stem from the painting but from the varied experiences, backgrounds, cultures and histories the observers bring with them. The same is true in data analysis. It’s through different points of view that something can be fully analyzed. Each person brings their varied experiences (their data) to the analysis.
As businesses we tend not to sit silently and take in what others see about ourselves and our data. We tend not to expose our data at all to our partners, trusted third parties or potential collaborators (like our customers) and by not doing so, they cannot combine their data with ours and uncover things we cannot see. As a result, we cannot see the broader picture. And this leads to bad business decisions based on a myopic point of view.
According to The Data Warehousing Institute, bad data decision-making costs US businesses $600 billion annually. The typical enterprise best practice for business intelligence (BI) is to sit in a room examining our historical corporate data. Yes, we mix this with acquired third-party insights such as industry-aggregated data, weather and seasonality statistics, and public records. Increasingly we are adding in real-time data from social media or other sources. These are all good moves. But when we are the only ones who look at the data we blind ourselves to more than half of what it could tell us. Our biases, our existing business practices, our operational processes inform but at the same time cloud our view into the data.
Want to fix this shortcoming? Open it up. Your data, with some cleansing and controls, can be shared with third parties who can look at it from their different points of view. Netflix leveraged this idea to improve its recommendation engine when it opened up this data set and incented developers to submit better algorithms than they could come up with themselves. American Airlines did this when it held a hackathon at South by Southwest and got back tens of new features and capabilities it could add to its website and mobile app. This concept lies at the heart of the open source movement – which you may well have participated in as a contributor adding capabilities or suggesting improvements based on your needs and points of view.
Gaining the ability to adapt to what others can see, sharing with third parties and collectively going new places is the next step we all must take in business intelligence. A step we at Forrester call Adaptive Intelligence.
In our latest report for CIO clients, I and my cross-role research collaborators, Eve Maler from the security team and Fatemeh Khatibloo from the marketing side of Forrester, lay out a path you can take to evolve from the mode of static intelligence you are likely engaging in today, to one centered around collaboration that yields real-time, multi-directional insights (see chart below).
In it we detail leading enterprises that have already moved down this path, including Pacific Gas & Electric, Kaiser Permanente, Lowe’s and New York City, and the business gains they have achieved through Adaptive Intelligence. We also provide guidance on how to prepare your data for sharing and discuss vendors solutions such as the Xignite financial platform, Microsoft’s Windows Azure Data Market and dunnhumby’s retail offerings that can accelerate your moves to Adaptive Intelligence.
As CIO, you play a crucial role in preparing your organization for this maturation – as you are the steward of corporate data. That stewardship has been driven historically by priorities around protection, recoverability and integrity of that data. To move to Adaptive Intelligence, you will have to think differently and change these priorities. We aren’t suggesting you stop protecting the data but instead think about data anonymization, security through aggregation and push toward a model that enables data sharing. It’s one thing for the business or marketing side to want to share data. It is another to operationalize this thought, and that is where you must step up. This change will require a move away from hoarding data, to becoming a librarian and treating data as a product.
In our surveys of business leaders, when asked what they want you, the CIO, to prioritize, the top of the list is to help them make better decisions with corporate data. You have been given the clear mandate. We can help you make the transition to Adaptive Intelligence. Take the opportunity that lies before you. And do it before your competitors take similar action.
Related Forrester Research
Search Forrester's Blogs
The dynamics that will shape the future in the age of the customer »
Planning for innovation and risk in the wake of Brexit »
Forrester's CX Index
Predict how actions to improve CX will affect revenue performance.
Measure the customer experiences that matter most »
- Amy DeMartine (7)
- Andre Kindness (32)
- Christopher Voce (8)
- Dave Bartoletti (28)
- David Johnson (52)
- Doug Washburn (37)
- Eveline Oehrlich (17)
- Frank Liu (10)
- Glenn O'Donnell (30)
- JP Gownder (109)
- Laura Koetzle (1)
- Lauren Nelson (11)
- Michele Pelino (6)
- Milan Hanson (3)
- Naveen Chhabra (2)
- Richard Fichera (149)
- Robert Stroud (12)
- Sophia Vargas (7)
- Stephanie Balaouras (1)