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Tag Archives: BI

Strategy and Market forces – Get your ducks lined up

10 Friday Oct 2014

Posted by Martyn Jones in Data Warehouse, market forces, nine competitive forces, Strategy

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Behavioural Economics, BI, Business, business analysis, Business Management, business strategy, Challenges, corporate assets, Creativity, Crisis, Data Warehouse, Dogma, Goal Setting, Information Technology, marketforces, operationalwareness, Strategy

Strategy and Market forces – Get your ducks lined up

Let’s now take a brief look at my ‘nine competitive dimensions’  model.

This model will be familiar to some who will readily connect with the inclusion of government as an environmental dimension.

Continue reading →

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Operational awareness isn’t for wimps! So, get it right

08 Wednesday Oct 2014

Posted by Martyn Jones in awareness, Big Data, business, Business Intelligence, Data Warehouse, operational, pig data, Strategy

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Analytics, Banking, Behavioural Economics, BI, Big Data, Business, business analysis, Strategy

I frequently include the term Operational Awareness in talks.

I think it’s important for strategy.

So I wrote a piece that tried to convey what I mean by the term.

But first, a diagram:

Image1

Figure 1 – Operational awareness

This is a simplified high-level example of business data objects found in certain organisations. In the above diagram I have reused an industry example of nine business data objects to represent operational data[1].

For completeness and to maintain rationality in this section here follows a summary list of the nine key groups of business data needed to have a coherent and cohesive operational awareness (these data groups are also frequently referred to as business data objects):

  • A: Party embodies all of the participants that may have contact with the organisation or that are of interest to the organisation and about which the organisation maintains data. This includes data about the organisation itself; data about external organisations; data about external and internal individuals; and, data about the roles of involved parties.
  • B: Arrangement represents a prospective or existing agreement, between two or more individuals, organizations or organizational units that provides and affirms the rights, rules and obligations associated with a transaction between parties.
  • C: Condition describes the specific requirements that pertain to how the business is conducted and includes information such as prerequisite or qualification criteria and restrictions or limits associated with the requirements. Conditions can apply to various aspects of an enterprise’s operations, such as the operational parameters of a resource item, the sale and servicing of products, the determination of eligibility to purchase a product, the authority to perform business transactions, the assignment of specific general ledger accounts appropriate for different business transactions, the required file retention periods for various types of information kept by an enterprise and the selection criteria for a market segment.
  • D: Product/Service describes the services, merchandise or facilities that can be offered, sold or purchased by the enterprise, its competitors and other Involved Parties during the normal course of its business. This concept also includes goods and services that are of interest to the enterprise such as supplies for manufacture.
  • E: Location covers a place where something can be found, a destination of information or a bounded area, such as a country or state, about which the enterprise wishes to keep information.
  • F: Classification is used to organize and manage specific business information by defining structures that represent classification categories. Classification also organizes and manages groups of business concepts that apply to multiple concepts.
  • G: Business Direction/Organisation Direction refers to and records expressions of a party’s intent with regard to the manner and environments in which it wishes to carry out its business. Business direction items contains, keeps data about, and is used to support the enterprise’s business and financial plans, policies, procedures and schedules.
  • H: Events describe a happening about which the organisation wishes to keep information as a part of carrying out its mission and conducting its mission.
  • I: Resource object includes and describes any value item, either tangible or intangible, that is owned, managed or used by, or of specific interest to, the organisation in the course of accomplishing its mission.

The key facets of operational awareness detailed above constitute a potential of fundamental importance in the formulation of organizational strategy.

Timely, accurate and appropriate data at this level can temper ambition with the facts on the ground, with operation insight, and with the effectiveness of time and place utilisation.

But take care. In most organisations there will be a spread of attention to the key facets illustrated here, and they will be treated with varying degrees of intensity relative to their overall contribution to strategy formulation. In addition, organizational specific facets may also be introduced where needed in order to complement the overall set of operational awareness facets described here.

[1] IBM’s IFW/BDW.

Business Intelligence Principles: If you don’t like them we have others

03 Friday Oct 2014

Posted by Martyn Jones in Best principles, Business Intelligence, Peeves

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Behavioural Economics, BI, Big Data, business intelligence, Business Management, business strategy, Demagogism, Dogma, enterprise data warehousing, Information and Technology, Offshoring, Organisational Autism

These are my principles for successful Data Warehousing and Business Intelligence, and if you don’t like them, I have others. Musings on being led by the nose by experienced practitioners of charlatanry, deception and obfuscation.

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Mugged in Data Hell – Perils of embracing the Faustian Side of IT – Part 3

03 Friday Oct 2014

Posted by Martyn Jones in Business Intelligence, Data Warehouse, Process

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Behavioural Economics, BI, Big Data, Business, Business Enablement, Business Management, Demagogism, Dogma, enterprise data warehousing, Information Technology, IT Strategy, MDM, Offshoring, Organisational Autism, Outsourcing

Continued from Part 2 which can be found here -> Part 2

I look over at Crème, who is now staring out the window watching the rain. I cough, theatrically, for effect. “So, Crème, would you like a rest, or do you want to tell us about what happened next?”

“Oh, yes” Crème says, “Sorry, I was wandering there for a while”. She continues.

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On your way to Data Warehouse success? We’ll put a stop to that!

01 Wednesday Oct 2014

Posted by Martyn Jones in Architecture, Best principles, Big Data, Business Intelligence, Data Warehouse, Excellence, Inmon, Peeves

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Behavioural Economics, BI, business analysis, Business Enablement, Business Management, data integration, enterprise data warehousing

One of the most soul destroying moments in the life of a data warehouse professional is when a key decision maker (usually backed by other key decision makers) decides to radically alter course, and “in a dance as old as time”, snatches defeat from the jaws of victory.

This can happen in various ways, but the most gut wrenching of all is this.

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Baby Naming and Religious and Social Trends – Big Data says…

01 Wednesday Oct 2014

Posted by Martyn Jones in Big Data, Knowledge

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Behavioural Economics, BI, Business Enablement, Organisational Autism

As legal sources close to the Westminster Bar would have it, an alleged fan of Stewart Lee, a leading English social commentator, writer, director, musician and stand-up comedian, has called on the power of big data outcomes to highlight changing demographics and to place hot-topic issues of people and society in the public forum.

According to Stew’s fan – and I’m sure he might correct me if I have this one arse over tit – the ultra-conservative intelligentsia have discovered that the most popular name for new-born children in the UK is not in fact Bellender, but Mohamed – and that’s just the girls.

Of course, this may be an unfortunate case of intermittent misrepresentation and big data viral incorrectness ‘gone mad’, but I would love to hear what Little Richard’s John has to say about the matter.

Many thanks for reading.


File under: Good Strat, Good Strategy, Martyn Richard Jones, Martyn Jones, Cambriano Energy, Iniciativa Consulting, Iniciativa para Data Warehouse, Tiki Taka Pro

We had to do something – Massive DW/BI/IT Fail

27 Saturday Sep 2014

Posted by Martyn Jones in Business Intelligence, Data Warehouse, Peeves

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BI, Business Enablement, business intelligence, Business Management, enterprise data warehousing, IT Strategy, Organisational Autism

In a city centre office block, somewhere in Scotland, the conversation between the IT Business Manager (Bill) and the Information Management Manager (Richie) is in full swing,, Bob is irate because his successfully delivered data mart has been derided as unusable rubbish by the business people it was meant to serve.

Let’s join the conversation: Continue reading →

Build it and they will come

21 Sunday Sep 2014

Posted by Martyn Jones in Business Intelligence, Data Warehouse, Extract

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BI, Business Enablement, business intelligence, business strategy, data integration, enterprise data warehousing, information management, MDM, Organisational Autism, Requirements management, Strategy

Extract taken from the draft work-in-progress provisionally titled Assess! Choose! Act! Data Warehousing and Strategy by Martyn Jones, Chief Strategist at Cambriano Energy.

For more than 34 years I have been trying to convince IT organisations that it is not in their best interests to play Santa Claus, especially when it comes to strategy and data management.

P4090224.m

I have tried – again and again, to make people pay attention to this advice, because I think that acting upon this take-away in an intelligent manner is absolutely central for the success of IT, for the benefit of business, and ultimately for the effective realization of Information Management; whether that is Data Warehousing, Business Intelligence, Data Integration, Decision Support, Data Analytics, Big Data or MDM.

Continue reading →

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