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How data governance leads to lean processes?

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  • How data governance leads to lean processes?

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    “Perception vs Reality” OR “How data governance leads to lean processes”
    “What are the odds of a hole-in-one during a Golf tournament? 100-1? 200-1? 1000-1?”. This was the general question asked of small independent bookmakers in Great Britain and Ireland by the “Hole-in-One Gang” in 1991. When it came to place the bet, they refined the question to “What are the odds on a Hole-in-One occurring in 4 specific professional tournaments, including the US and British Opens?”

    They chose small independent bookmakers as they would not have the data available to them to make an informed estimate and the gang knew if they could get a quote it would be based on the perception of the bookmaker.

    The odds of a Hole-in-One in the amateur game is estimated to be around 12,500 to 1 according to insurance companies who cover such events. In the professional game, however their estimate is an amazing 2 to 1 or 50%. This is because the golfers taking part are the best players in the world and there are normally around 144 of them in a tournament. Furthermore, as the courses they play normally have 4 short holes in the 18 holes they play, the leaders get 16 attempts during their 4 rounds. Overall (assuming half the field plays all 4 days) there are over 1,700 opportunities available to individuals skilled at driving the ball close or even into a hole!

    However as most small book-keepers did not have the data they needed to quote the correct probability, they used their own experience, anecdotal evidence and their perception of the risk to quote odds of around 100-1. During the documenting of the story the odds of at least one “Hole-In-One” in each of the named tournaments were calculated as just 30-1. Using a series of combination bets of two, three and the four tournaments, the ‘Hole-in-One Gang” made £400,000 in three months which would be around $1.3 million dollars in 2017.

    Some bookmakers paid up, some went bankrupt and some just disappeared without paying. The lack of data to back up the odds quoted should have stopped the bookmaker taking the bet, however this event demonstrated that human perception and nature (they were bookmakers after all!) are powerful factors in decision making.

    The story just goes to show how perceptions, anecdotal evidence or even gut feelings often differ from reality and can wrongly influence business into making the wrong decision or developing inefficient processes.

    When you listen to executives talk about their companies, they usually speak about memorable events in the history of theirClick image for larger version  Name:	22.JPG Views:	1 Size:	14.0 KB ID:	118
    company where they:
    • closed an amazing deal to sell a large quantity of their product
    • had a significant delivery problem or a product malfunction
    • launched a new product successfully.
    They talk about extreme conditions rather than the daily running of the company, (well who wouldn’t!)

    In reality, a company’s success is usually achieved through efficient, standardised and repeatable processes.

    Today, most companies look to achieve efficient processes using the Lean approach to process improvement. This approach relies heavily on the initial gathering of information about the processes within a company.

    Improvements are made using a 5-step approach called DMAIC, where a company
    1. Defines its processes
    2. Measures its processes
    3. Analyses where there is added value and non-added value steps in the process
    4. Improves its processes by removing non-added value and improving added value
    5. Controls its processes through monitoring
    Once the organisation has defined a process it wants to improve, it needs to accurately measure the steps of the process
    This is the most vital step of the approach and the one that can most benefit from a Data Governance Framework

    If the measurement phase is poorly defined or executed, subsequent analysis will derive inaccurate or flawed findings, improvements will be incorrectly scoped or developed and any performance metrics will misrepresent how efficient the new process is.

    A Data Governance Framework will support the measurement and understanding of a process as it provides an approach to defining data elements, documenting possible values and developing rules for a process to follow. If a framework does exist it is possible to ask
    • Do we have enough data about the process in question? (inputs, outputs, successful outcomes, drop-out rates, process failures, post process problems)
    • Do we have data on all the possible values that that can enter the process? (different inputs at different times)
    • Do we have consistent data definitions for time and frequency so that everyone understands what is presented as elapsed time or wait time? (end to end, each step and between steps)
    • What are the current Key Performance Indicators (KPI’s) of the process and is the current underlying data accurate? (Can the data reconcile to other KPI’s?)
    The implementation of a Data Governance Framework ensures that the current reality of the company influences Lean process improvement rather than perception, anecdotal evidence or ‘gut’ feeling.
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    For instance

    The memorable sale could turn out to be a singular event that has influenced the way all sales are handled, when in fact the additional activity performed on that occasion is an excessive overhead for all other sales.

    The significant delivery problem may have added several checks to the delivery stage of the process that are not required in most cases.

    The launch of a new product whilst perceived as successful, may have impacted the end to end process for all existing products and made their production less efficient.

    It is often the case that current processes within a company are initially well defined and efficient but evolve over time because of an addition of new inputs, changes to regulation or company policy, as well as over-reactions to ‘memorable’ events.

    Perception of what is causing process inefficiencies is often used to start process improvement initiatives, however processes really become ‘lean’ through accurate and consistent measurement of all factors that support the process.

    Accurate and consistent measurement of a process produces a clear picture of the reality of the situation.

    Accurate and consistent measurement occurs when a fully defined set of data elements, values and associated rules are in place as part of a Data Governance Framework.

    Therefore, a Data Governance Framework allows improvements to be identified and processes to become ‘lean’ again.

    A well-implemented Data Governance Framework supports the definition of reality and ensures that the correct data is available, understood, stored, analysed, maintained and reported allowing lean process improvement to flourish and support the implementation of the improvements required, rather than those suggested or perceived.
    Paul Lunn, November 2017

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    Paul Lunn has been and Independent Consultant and Managing Director of Lunn Consultants since 2012.
    With over 35 years’ experience of change in Finance, Banking and Insurance, Paul has worked to deliver business change as a programmer, systems analyst, project leader, account manager, senior business analyst and consultant.
    Drawing on his real-life experiences of change (from strategy definition to implementation and beyond), Paul is now sharing best practice through consultancy work, lecturing and is currently developing an on-line course to promote best practice for professionals involved in change.
    For further information, please contact Paul at
    LinkedIN Email [email protected]

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