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What went wrong at Digg: publishers, PR hacks and power users ruled the roost

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mouser:
From BoingBoing today, comes a short piece on the collapse of the website digg.com.

Note: I wrote a longish piece attaking the digg model in 2006, back in it's heyday, and I wasn't the only one; see How Digg Gets Everything Backwards.. And How to Fix It .

The only way to consistently get stuff on the home page was to work at it like a job. ... everyday users were realizing that nothing they submitted ever even had a chance in hell of going to the front page. They weren't empowered netizens visiting from the future, but chumps who were being played by Digg and a bunch of "social-media consultants."

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http://www.theatlantic.com/technology/archive/2012/07/the-big-digg-lesson-a-social-network-is-worth-precisely-as-much-as-its-community/259770/





from http://boingboing.net/2012/07/13/digg-dug-own-grave.html

IainB:
You could well have been right in what you said in that older (2006-09-07) DCF discussion that you kicked off.
I don't feel qualified to comment though, as, though Digg, StumbleUpon, and the other all-the-samers looked intriguingly interesting to me at first glance, I could never really understand what they were really supposed to be, nor see the point/use of them for me or other users. Same with Google's Wave or Buzz or Google+, for example. They seemed nebulous.
Don't get me wrong - I did have at least some understanding of their fly-paper-like business objectives, but that was probably all.

When I read that theatlantic.com article though, I thought it was so busy analysing and criticising Digg - in hindsight and after the fact - that it could well have missed the point about the lack of definition (nebulousness) of Digg.

I would approach that from a theoretical perspective: (because it tends to stand up in practice)

* Function and purpose: Any business generally exists merely to do something in such a way as to enable it to make a profit from what it does, to maintain/increase shareholder value. (Conventional business model.)
* Process: What a business does can be defined as a process. If you are unable to define it as a process, then you don't know what it is that the business is doing. (W.E. Deming.)
* Process capability maturity: If you can attempt to define it as a process - for example, (say) using the GAO-preferred IDEF0/3 methodology (GAO BPR Assessment Guide 1997), with ICOMs (Inputs, Controls, Outputs, Mechanisms), but in a state where the ICOMs vary in the short term, then the Quality of the Output will tend to be subject to inherent statistical variability/inconsistency. (W.E. Deming.)
* CMM Levels: This state of variability was defined in the 5-level Humphreys CMM (Capability Maturity Model) as Level 1 (Ad hoc) or Level 2 (Repeatable). Level 3 (Defined) was where you operated the processes consistently in a defined manner. Level 4 (Managed) was where you deliberately managed the processes (as distinct from managing the business), and Level 5 (Optimised) was where you optimised those managed processes. (Managing the Software Process, 1989, Watts Humphrey)
* Processes in statistical control: These are processes where the process performance (e.g., the quality of a process Output) can be seen to be in statistical control and subject to Common Causes inherent in the process itself. There are no trends, the mean is flat, performance is consistent and repeatable, and any variability beyond normal Upper or Lower performance bounds is thus attributable to Special Causes. (W.A.Shewhart)
* Processes out of statistical control: These are processes where the process performance (e.g., the quality of a process Output) can be seen to be out of statistical control and subject to Special Causes. There are trends, the mean moves all over the place, performance is inconsistent and not easily repeatable, and process performance is almost entirely attributable to Special Causes (e.g., the process changes). (W.A.Shewhart)
Deming showed (in "Out of the Crisis: Quality, Productivity and Competitive Position" 1982) that where a business' core business processes were out of Statistical Control (which would typically place them in Humphreys' CMM Level 1 or 2), then they would progressively be likely to:

* Fail to make sales.
* Lose customers.
* Lose market share.
* Make a net loss.
* Go bust.
If you look at Digg and other recent innovative Internet-based businesses that seem to have failed (including those within Google), you are likely to find that they generally seemed to involve a poorly-defined business process and/or a process in a dynamic state of change. This would place them as business processes out of Statistical Control, in Level 1 or 2 of the CMM.
With a dreadful statistical certainty, it seems that they must fail.

There could be other examples in progress - e.g., interestingly, to an onlooker, Facebook might seem as though it is making all the right moves to follow suit.
Generally, if a business has a single major core business process, then such a process failure is likely to be a recipe for disaster. If they are not yet core processes, and are being exposed to the market as ß-tests in a sandbox (e.g., like Google Wave, Buzz, etc.), then the costs of failure would probably be written off as necessary market trialling or R&D costs, well before they started to adversely affect overall corporate profitability or shareholder value.

TaoPhoenix:
Wow Iain, that post is incredible.

IainB:
Wow Iain, that post is incredible.
-TaoPhoenix (July 14, 2012, 08:03 AM)
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Hahaha - does that mean you don't believe it?    ;D
(Don't bother answering. It's a rhetorical Q. I don't ask for or expect belief.)

My training for improving or re-engineering business processes typically involves:
(a) gaining an understanding of the process by applying relevant theory to the process, then
(b) actions in line with that theory, to improve the process.
"Action which is not based on sound theory or "best"/good practice is irrational by definition." (WE Deming)

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What I learned from studying Deming et al was that, for improving existing processes, if you focussed on the the ICOMs and the cost-effectiveness of process design, by modelling the AS-IS and TO-BE processes and applying (say) ABC (Activity-Based Costing) or Linear Programming/Optimisation (where the latter might be feasible/relevant), then you could usually streamline your process design on "paper" (I use computer-based models) before spending a lot of money introducing risky ad hoc changes to the actual process. This saves time and money, and reduces potential risk of a costly screw-up.

Of course, one piece of theory to apply is about processes in CMM Level 1 or 2. That is, you should try to avoid potentially wasting your time by putting any work into a process until it has been brought under Statistical Control (CMM Level 3 or above). It is axiomatic that only when an AS-IS process is in Statistical Control can you rationally develop a plan to improve its design.

So, when I read about "Where XYZ business went wrong", my approach is to focus on the ICOMs in a model of the processes involved, and not what I think/feel should be done about symptomatic or organisational problems. Theory is a powerful thinking tool for discovering truth, and it invariably leads us to the realisation that the causal problems in business are generally to be found within a business process. Every time a coconut.

TaoPhoenix:
Wow Iain, that post is incredible.
-TaoPhoenix (July 14, 2012, 08:03 AM)
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Hahaha - does that mean you don't believe it?    ;D

-IainB (July 14, 2012, 10:53 AM)
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Of course I believe it - it and the followup were at a high level, higher than most posts I've seen anywhere. Looks like you took some management training either at work or elsewhere.

It's especially funny if you look at the thread starter pic.  ;D

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