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Data Delivery Dysfunction - The Diagnosis

Posted by Datasource on Jul 1, 2016 2:48:00 PM

The following came out of some corner of my oddball brain where characters like Hector Bison, a corporate Business Intelligence Director and Doctor Data carry on somewhat amusing conversations about Data Delivery Dysfunction. The following takes place in an exclusive, remote Data Crisis Clinic (DCC) clinic where business and IT leaders are treated with the utmost discretion and tell the truth about their actual experience and results working with their organizations to deliver the right data, to the right people, at the right time to enable the right decisions. Any similarity to real persons or organizations living, dead, or in some zombie-like state is purely coincidental.

AssetDoctor Data (DD): Welcome to the Data Crisis Clinic where we work with you to help you optimize the business value of your data. What seems to be the problem?

Hector Bison (HB): Well doctor, if I knew that I probably wouldn’t be here. It’s pretty embarrassing - everything we talk about is covered by doctor-patient privilege, right?

DD: Absolutely. This will never, ever be shared with anyone – not even in the blog post of a lunatic.

HB: OK then. We have invested a lot of money and time, hoping to get more value out of our data. We have all the latest technology and tons of data from across our systems, from social media and external sources and we’re more agile than a mongoose. I feel like all our efforts have just landed with an empty thud. Based on what I read and what our data technology vendors told us while we were developing this, I thought by now I would be basking in the praise of my colleagues, courted by top-flight executive recruiters, on the cover of Wired, written up in the Harvard Business Journal, and that my friends would start calling me the Duke of Data instead of what they call me now.

DD: What do they call you now?

HB: (Groan) Data Monkey.

DD: Well with that moniker, we need to get you some help stat. Let’s explore your symptoms so we can diagnose your problem. How would you characterize the level of trust between members of the business intelligence team and with the people in the business who want to use BI?

HB: Hmm, I guess I’m not sure. The requestors don’t seem to share more information than they think the BI team needs and the BI team are frustrated that the business users don’t use the BI applications. The requestors also request the same thing from multiple BI teams because they don’t trust one team to deliver. I would say it’s not that great.

DD: OK. Is there much conflict between stakeholders over data?

HB: Yikes, that’s hard to answer. There are times I think all we do is disagree over data, but it doesn’t really manifest in conflict. It’s mostly just departments driving the exec team crazy by showing different versions of the numbers, either out of ignorance or hoping to discredit another part of the organization. I guess we figure if we’re not in open conflict we won’t have to resolve it.

DD: What’s the level of commitment of the stakeholders to the BI efforts, and of the various stakeholders to optimizing the value of the data?

HB: Are you familiar with the story of the Little Red Hen? When she decided to bake some bread, none of the other animals would help make it, but they all wanted to help her eat it. I feel like that’s our story – people are united in their desire to have the data, but not in doing the work to get it. User acceptance testing is typically done by the development team, because the users don’t have time.

DD: Is there clearly defined accountability for data and data-related tasks in your company?

HB: Well, we’ve talked about data governance and data stewardship, but the majority of people don’t feel that would work in our culture – at least not yet.

DD: OK, last question. Are your BI efforts tied to clearly defined business results?

HB: Well, like I said at the beginning we don’t really seem to be leveraging what we’ve built so, I guess not. Hey wait, you haven’t asked me any questions about our fabulous technology!

DD: I didn’t need to, because I already have a diagnosis and I charge by the hour. As we’ve been talking, our predictive analytics model has been digesting the audio and video from our conversation, the online questionnaire you completed yesterday, your corporate profile, the vendor websites with your logo on their customer page, the Twitter streams from your top three layers of management, and news feeds about business opportunities your company has missed over the last five years. Based on our analysis, it looks like you won’t have much money for our bill, so I would like to get right to it. Would you agree that delivering BI is not a solo act, that it requires a team?

HB: Gee, doc! First of all – wow! Can you show me how your system works? Is it all in-memory processing?

DD: Hector, focus. Delivering BI successfully to really make the kind of difference you expected to see – does it require a team, a team that extends beyond the boundaries of your BI organization?

HB: Sorry doc. Yes, even with a team it’s definitely a challenge.

DD: Are you familiar with Patrick Lencioni’s five dysfunctions of a team? They are:

  • Absence of Trust
  • Fear of Conflict
  • Lack of Commitment
  • Avoidance of Accountability
  • Inattention to Results

Bob, I’m afraid your company has Data Delivery Dysfunction. Technology can be a powerful enabler, but it can’t overcome all the obstacles you have to effectively deliver and optimize the value of your data.

HB: Gadzooks, Doc! That sounds horrible. Is it terminal?

DD: It can be, but with proper holistic treatment a cure is possible.

HB: Woohoo! What a relief. What’s the prescription? PowerPoint slides and a meeting with the C-suite?

DD: It’s nice to see you haven’t lost your sense of humor, Hector. We can discuss that in our future sessions. Before our next session, think about those different aspects of dysfunction on your team and how you personally might be contributing to it.

What’s your Data Delivery Dysfunction?

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BY: GRANT SUTTON | DATA GOVERNANCE PRACTICE LEAD

Topics: Data Governance, Blog

Written by Datasource