Data’s aspiration towards operational excellence sounds much better, more concrete than some vague notion of delivering “insights”.

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That’s precisely why I wanted to redirect the mission.

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Hi Ergest,

I am currently working on the 2nd edition of my book Data Humour which contains collection of humorous data quotes related to data, big data, statistics, and data science, from different sources and a wide array of cultural figures, thought leaders and key influencers across the world.

I would like to include your statement with your name in the book-

"Analytics professionals have always seen themselves as oracles of business insights, advisors and strategic partners who deserve a seat at the main table, but that’s not how they get treated."-ERGEST XHEBLATI

Please let me know if that is OK with you?



Link to the first edition- amazon.com/Data-Humour-Statistics-Science-Punchlines-ebook/dp/B09N2NW22J

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Hi Rupa, that’s perfectly fine thank you

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Jun 23, 2023Liked by Ergest Xheblati

I love your connection to Wardley Maps.

I would like to respectfully and excitedly tell you that this statement is only HALF of the equation: "The ultimate goal for analytics is to drive operational excellence."

If I add the bit I'm thinking of you get: "The ultimate goal for analytics is to drive rapid strategy execution and operational excellence"

I'm an "OKR Coach" (OKRs = Objectives and Key Results). I teach the OKR framework that was used originally by Intel then Google to grow their companies into the monsters they are now. Many of the top companies now use some sort of goal framework (those that don't, should!)

How do OKRs relate to data and your goal statement?

OKRs basically 'deploy strategy'. They allow you to take a valuable slice of your strategy and execute it (the trick is that they align dozens or even thousands of teams across silos to work towards a common goal)

O = Objective

KRs = Key Results (there are usually 3 to 5 KRs):

Each KR has a metric value 'starting value' and a new 'target value' (that we're aiming to move the metric to over the next (say) 3 months)

The best way to setup your KRs is to have some lagging metrics and some leading metrics. Abhi Sivasailam calls them "input and output metrics" but that sounds like the relationship/correlation is a bit too 'gauranteed' to me like plugging numbers into a formula or a items on factory conveyor belt (put thes parts in and you get that part out) so, like many OKR coaches, I use "leading and lagging metrics".

If you have leading and lagging metrics then you need to have a (from your Wardley sequence) "concept", "hypothesis", "theory" on which leading metric correlates to the lagging metric you really care about.

SIDE NOTE: Hypothesis means "educated guess" so I'd say the word that comes before that (in the Wardley sequence) isn't "concept" but perhaps it's "guess". What do you think?

So in summary the process of strategy execution is:

* Vision

* Strategy

* Results Map

* OKRs

* metics trees <<< this data is a fundamental foundation of stretagy execution - without a mature understanding of how leading and lagging metrics correlate to each other you're guessing as to what activity to do in order to execute on your strategy

BTW: I found you from this post on LinkedIn https://www.linkedin.com/feed/update/urn:li:activity:7076303052571320320?commentUrn=urn%3Ali%3Acomment%3A%28activity%3A7076303052571320320%2C7076303507376467968%29&dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287076303507376467968%2Curn%3Ali%3Aactivity%3A7076303052571320320%29

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You should write a post about this.

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I know - time is limited and I'm bit of a perfectionist which makes it hard to finish blogs! Darn it.

What do you think of my question: Hypothesis means "educated guess" so I'd say the word that comes before that (in the Wardley sequence) isn't "concept" but perhaps it's "guess". What do you think?


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I would get hung up on definitions. Wardley doesn’t spend much time with knowledge evolution, he’s mainly focused on components. I’d focus more on the discovery of “input metrics” aka leading indicators and how they drive OKRs.

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