So, this blog is dedicated to stepping outside the comfort zone once again and into the world of chaos. Not only may you not want to persist in your data quality transformations, but you may not want to cleanse the data.
Current thinking: Purge poor data from your environment. Put the word “risk” in the same sentence as data quality and watch the hackles go up on data quality professionals. It is like using salt in your coffee instead of sugar. However, the biggest challenge I see many data quality professionals face is getting lost in all the data due to the fact that they need to remove risk to the business caused by bad data. In the world of big data, clearly you are not going to be able to cleanse all that data. A best practice is to identify critical data elements that have the most impact on the business and focus efforts there. Problem solved.
Not so fast. Even scoping the data quality effort may not be the right way to go. The time and effort it takes as well as the accessibility of the data may not meet business needs to get information quickly. The business has decided to take the risk, focusing on direction rather than precision.
While you no doubt answered wellness, the reality is that when you look at the typical change programs in a major corporation today, Band-Aids are far more common. But that's hardly surprising given the short-term pressures facing organizations today. Let's reflect on a few examples:
Those in the financial services industry are still struggling to deal with the rash of new regulation post meltdown. Following a spate of high-profile failures, risk management has taken center stage, while in others there is a hurried review of operating procedures in far-flung corners of the corporation.
In virtually all industries, others are trying to respond to hemorrhaging sales statistics. Customers are no longer happy to keep quiet when they get a bad service experience - they tell their friends and followers via Facebook and Twitter. Customer churn is rampant.
Or is it increased competitive pressures? More and more new entrants are turning up to challenge and disrupt the incumbent business models of many established firms. They don't have the baggage of high-cost business models and 12 layers of management.
Arguably, mobile is currently the hottest trend driving both business and technology strategies for executives. If you need any additional evidence, just look at all of the enterprise buzz Apple has generated with the iPhone 5 launch. Unfortunately, today’s business and technology leaders continue to respond to the mobile opportunity with the wrong answers. Business leaders respond to mobile with, “Let’s build a really slick mobile app, put it up on iTunes and we’re done!” Technologists respond to mobile with, “We need a strong BYOD policy and to put device management tools in place!” Both of these responses completely overlook the fact that underlying legacy applications and business processes need optimizing for the mobile experience.
We run into examples of this “lipstick on a pig” approach to mobile all the time. In fact, I ran into a perfect example of this recently when I needed to order a pizza for my family after a very hectic Saturday afternoon. When I picked up my mobile phone to call the pizza delivery place, a light bulb went off over my head. Instead of dialing the pizza delivery company and waiting on hold for 15 minutes, why not download its mobile app in two minutes and order my pizza within another two minutes. I figured I could shave off ten minutes of wait time by simply downloading the pizza delivery company’s mobile app.
Enterprise architects I talk with are struggling with the pace of change in their business.
We all know the pace of change in business, and in the technology which shapes and supports our business, is accelerating. Customers are expecting more ethics from companies and also more personalized services but do not want to share private information. Technology is leveling the playing field between established firms and new competitors. The economic, social, and regulatory environment is becoming more complex.
What this means for enterprise architects is that the founding assumptions of EA — a stable, unified business strategy, a structured process for planning through execution, and a compelling rationale for EA’s target states and standards — don’t apply anymore. Some of the comments I hear:
“We’re struggling with getting new business initiatives to follow the road maps we’ve developed.”
“By the time we go through our architecture development method, things have changed and our deliverables aren’t relevant anymore.”
“We are dealing with so many changes which are not synchronized that we are forced to delay some of the most strategic initiatives and associated opportunities.”
The bottom line is that the EA methods available today don’t handle the continuous, pervasive, disruption-driven business change that is increasingly the norm in the digital business era. Our businesses need agility — our methods aren’t agile enough to keep up.
We last spoke about how to reboot our thinking on master data to provide a more flexible and useful structure when working with big data. In the structured data world, having a model to work from provides comfort. However, there is an element of comfort and control that has to be given up with big data, and that is our definition and the underlying premise for data quality.
Current thinking: Persistence of cleansed data.For years data quality efforts have focused on finding and correcting bad data. We used the word “cleansing” to represent the removal of what we didn’t want, exterminating it like it was an infestation of bugs or rats. Knowing what your data is, what it should look like, and how to transform it into submission defined the data quality handbook. Whole practices were stood up to track data quality issues, establish workflows and teams to clean the data, and then reports were produced to show what was done. Accomplishment was the progress and maintenance of the number of duplicates, complete records, last update, conformance to standards, etc. Our reports may also be tied to our personal goals. Now comes big data — how do we cleanse and tame that beast?
Reboot: Disposability of data quality transformation. The answer to the above question is, maybe you don’t. The nature of big data doesn’t allow itself to traditional data quality practices. The volume may be too large for processing. The volatility and velocity of data change too frequently to manage. The variety of data, both in scale and visibility, is ambiguous.
I recently finished reading Moneyball, the Michael Lewis bestseller and slightly above-average Hollywood movie. It struck me how great baseball minds could be so off in their focus on the right metrics to win baseball games. And by now you know the story — paying too much for high batting averages with insufficient focus where it counts —metrics that correlate with scoring runs, like on-base percentage. Not nearly as dramatic — but business is having its own “Moneyball” experience with way too much focus on traditional metrics like productivity and quality and not enough on customer experience and, most importantly, agility.
Agility is the ability to execute change without sacrificing customer experience, quality, and productivity and is “the” struggle for mature enterprises and what makes them most vulnerable to digital disruption. Enterprises routinely cite the incredible length of time to get almost any change made. I’ve worked at large companies and it’s just assumed that things move slowly, bureaucratically, and inefficiently. But why do so many just accept this? For one thing, poor agility undermines the value of other collected BPM metrics. Strong customer experience metrics are useless if you can’t respond to them in a timely manner, and so is enhanced productivity if it only results in producing out-of-date products or services faster.
The pace of business change is accelerating. The reason why it is accelerating is the mushrooming of disruptive factors: your customers expecting anytime/everywhere access to you through their mobile devices, competitors leveraging big data technology to rapidly execute on customer-centric value propositions, and new market entrants with lean business models that enable them to outmaneuver your business.
Most companies deal poorly with disruptive change. If they are the “disruptor,” seeking to use these disruptive factors to steal market share, they often run without a plan and only after, for example, a poor mobile app customer experience, realize what they should have changed. If they are the firm being disrupted, the desire for a fast response leads to knee-jerk reactions and a thin veneer of new technology on a fossilized back-office business model.
This is where the value of business architects and business process professionals comes to play: you help your company plan and execute coherent responses to disruptive factors. That’s why your company needs you to attend Forrester’s Business Architecture & Process Forum: Embracing Digital Disruption in London on October 4 and Orlando, FL on October 18–19, 2012.
We’ll start with James McQuivey describing how technology is changing the playing field for disruption in his keynote: The Disruptor’s Handbook: How To Make The Most Of Digital Disruption.
We’ll look at how firms have used technology to rethink their operating models, eliminating low-value activities to focus on what their customers value in Craig Le Clair’s Implementing The Different In The Age Of Digital Disruption.