I was watching the late night news when a program that is shown at an earlier time The 7pm Project came on. I usually don’t watch at that time as I am watching the ABC news. This was on the Friday, 4th December.
Dr Karl was being interviewed about his science. There was an item regarding how all of mankind had originated from the east coast of Africa. At the end they were discussing the analysis of the data. Out of blue Dr Karl says, “Statisticians are the sluts of the maths world” as quoted by Adam Spencer. I have gone back to the original clip online but the segment has been cut out. I wonder why?
So there I was sitting, thinking I am a slut of the maths world. Hmmm. My sister would be laughing her head off if she heard anybody call me a slut! Something I cannot imagine, I don’t think anybody can. Making love with maths.
What is a slut? A floozy. I remember when I was young, being crazy in nightclubs and friends calling me a floozy, “go on, flitter away”. What was I doing? Going around and saying “hello” to all my friends in all areas of the club. Nothing wrong with that, I had a wide variety of friends with all different backgrounds.
If this is the case, that I can take my maths where ever I like, where people from all different disciplines know that I will understand them, know what they are trying to do with the numbers and they will understand my analysis. Then I don’t mind being called a slut of the maths world, not many people can say that they can understand maths which ever way you look at it.
So Adam, you are just jealous that I can take my maths to any discipline, whether corporate or research and any industry. Yes, I am a slut of the maths world but I am proud of being able to understand the numbers, interpret so people can understand and use the analysis in the manner required.
The Operations dashboard demonstrated that an organisation is able to split the decision and data, using profitability analysis to analyse decision in operations to mitigate short term risk of the business.
The business has to be able to apportion the different costs in all lines of business and market segments to the correct revenue stream. An internal transfer rate is a cost allocation that will apportion “To Build” costs by market segment.
The following set of diagrams will demonstrate the theory in allocating product costs to market segment using Internal Transfer Rates.
The colour index code can be followed as we drill down through each diagram in the model.
Figure 7. Corporate Decision Structure for business operations.
The corporate decision structure demonstrates the different levels of decision making. The CEO, other CxOs down to Line of Business and Market Segment are involved in the long term strategy of the organisation : CAPEX, aquisitions or reinvest into business, taxes, interest and intangible assets. This is why the CxO’s are paid the big dollars and bigger bonuses to ensure the business reaches the organisation’s 5 year plan.
Though, I don’t understand why some, undeservedly, get paid the big bonuses when these goals are not reached or before the end of the 5 years or their decision causes problems later on. “They” should make bonuses be paid over time, eg, the length of the investment decision made. Then “they” would have to suffer like the rest of us. Just my rant…
Business operations must align with the long term strategy of the organisation. To make the business operate the organisation needs all the solid blocks, above, to reach the long term goals but the business needs to mitigate short term risks within these blocks.
The business has to analyse the decisions made for product and relate the decisions to a revenue stream within market segment. There is a need to split all lines of business, decision and cost, into the different market segments. This is to ensure that decisions made for one product does not affect the market segments and other lines of business. The business cannot make decisions on the cost of one product only as market segments and lines of business are interrelated.
Figure 5. Level 2 Operations dashboard by Product by Market Segment. (in the ops dashboard , as by Market by Lines of Business).
The business also has to split the blocks of Line of Business in Figure 7 to be the proportions of the “to Build” and “Other Expenses (LOB)”, in figure 5. The business will build the product as a sum total of the business as it would be inefficient to have different production lines for different segments making the same product. These proportions will differ by market segment depending on demand.
Internal Transfer Rates
Internal transfer rates are costs that are allocated by line of business to the market segments. The internal transfer rate is to allow the analysis for product profitability by market segment. These rates are based on the total planned demand for the year and the total costs to operate the line of business.
The “To Build” and “Other Exp (LOB)”, in figure 5, costs will be initially allocated to all to build costs. The other expenses should not exist in a perfect business model that is working towards demand, if the business is over supplying, these excess capacities will be shown in other expenses.
Figure 8. Annual planned demand by market segment and budget cost to supply by product.
The internal transfer rate is based on total planned demand and total budget costs to build the product. The unit cost can allocate the total costs by the proportion of actual units sold by market segment.
Figure 9. “To Build” and “Other Exp (LOB)” cost allocation by market segment.
General Ledger vs Product profitability for costs at time point X.
The effect the transfer rate has on the product profitability analysis will show the actual costs based on actuals sales by product by market segment. The delta between the total actual cost from the general ledger and the calculated costs from the transfer rate will give the “Other Expenses (LOB)”.
Other Expenses (LOB) :
1. Will never be negative,
a) The business will always plan to have excess capacities for any unforeseen demand
b) To ensure service level agreements
c) Seasonal skews
d) Other costs to support the line of business
2. If negative,
a) The line of business is over charging market segments with the transfers rates and overstating initial costs, therefore budget costs for product are higher than the actual costs, and
b) There has been an unexpected windfall in cost reductions
Figure 10. Level 2 Operations dashboard by Market by Line of Business.
The profitability analysis for product by market segment show the actual costs “To Build” using actual units sold and the transfer rate. The General Ledger is able to apportion the costs into “To Build” and “Other Exp (LOB)”. The operations dashboard now has the additional margin analysis, Product Variable Margin. The business can now measure decisions made for product by market segment.
Conclusion
The internal transfer rate will apportion the “To Build” cost by market segment. This will allow the business to identify and mesure decisions made for product by market segment to mitigate short term risks in operations within product.
Seth Godin recently wrote “When data and decisions collide”. Over the next posts I will describe a model where decisions and data do not collide.
Organisations make decisions for the business based on reports from various sources. The long term objective of any profit-organisation is the business must be running to profit, otherwise no reason for business to exist other than for passion.
Revenue and costs are the key drivers to this objective. These decisions are made within the operations of the business to ensure the business is running to profit. Marketing strategies, supply and demand decisions and to service customer while running the business to long term strategies.
Most decisions are made reactive. The first question management asks “Why?” Everybody jumps to ensure at the current point in time that the business is not going towards plan. Usually means the sales team has to work harder or we cut costs to deliver the product to the consumer so people may lose their jobs.
This response to data does not take into consideration the reaction the decisions may have an effect on other parts of the business. There is no correlation between the market segments and the different products.
The following model will show that the data will allow the organisation to make concise decisions for the business without affecting other parts of the business. This model will use investor flow value and profitability analysis as inputs to decisions and then the decisions measurable on the profit and loss statement. This model only takes into account what is measurable in the profit and loss statement and does not take into account the outside the business environment intrinsic decisions stakeholders must take when making decisions, though these decisions will be minor with the analysis.
Measuring Operations
A dashboard is a set of metrics showing a business’s performance at a particular point in time. The model must be able to roll up and drill down to all levels of line of business, market segments and line items on the profit & loss statement.
An operations dashboard is to mitigate risks resulting from decisions in an organisation’s short term strategy for product, delivery and service without affecting the business’s long term strategy and profitability.
An operations dashboard for a matrix organisation is to ensure decision made in one customer segment and/or line of business will not affect the long term strategy of the business within market segment and line of business.
The following set of diagrams will show the theory in creating an Operations Dashboard, drilling down from the business model to the dashboard based on the investor value flow of the business’s decisions and profitability analysis.
The colour index code can be followed as we drill down through each diagram in the model. Purple – Investor interests Aqua – Decisions made by the business from investment to customer Navy Blue – Profit & Loss metrics Yellow – Decisions and Metrics related to Operations Light Blue – Decisions and Metrics related to Line of business Orange – Decisions and Metrics related to Market segment Dark Green – Operating Divisions
Figure 1. Investor value flow from investment to customer to return on investment.
The investor will invest capital in a company based on a long term strategy of the business and their products. The right side triangle is the “decision side”, showing as we build the product to the customer the business makes decisions on the end product. As the decisions are made the money from the capital investment which is now an operating expense is reduced as each step of the product is delivered to the customer.
The left side triangle shows profitability analysis using the profit and loss statement. The business generates revenue from the customer. Decisions for product, delivery and service made from the right triangle have costs associated with profitability including depreciation and amortisation on capital.
The business will make decisions on their capital investment based on long and short term strategies related on the customer and line of business which has an affect on profitability which in turn affects ROI for investor.
Figure 2. Investor value flow based on the individual components of business operations for a matrix organisation.
The ROI is based on the flow of decisions made by the business on individual components within business operations.
Decisions on capital expenditure, product costs are made by line of business. Decisions on delivery and service to customer are made by market segment. But these decisions are not independent of each other. Long term strategy and mitigating short term risks are interrelated to the market segment and the line of business.
Figure 3. Profitabilty analysis based on long term strategies by line of business.
The profit & loss metrics are based on the market segment and line of business. Figure 3, line of business dashboard, shows investor value flow to net profit based on capital expenditure. This is an indicator of long term strategies. Showing total operating profit based on mitigating short term risks and total profitability for the reporting period.
To seperate data and decision the business must also be able to seperate the cost by line of business to deliver the goods & services and the revenue stream by market segment.
Operations Dashboard
The metric used to measure operating performance is EBITDA as the depreciation and amortisation deals with the initial capital expenditure based on the line of business. The driver of EBITDA is revenue, revenue is generated by market segment.
The operation dashboard is an indicator of short term strategies are in line with the business’s long term strategy and will give a clear indicator of operating costs by market segment. Metrics are a combination of market segment and line of business.
Figure 5. Level 2 Operations dashboard by Market by Line of business.
The business is now able to separate decision and the metric by market segment, by line of business and by operating division.
The dashboard will allow each solid block in Figure 5 to be drilled down further into individual line items of the P&L of market segment and of line of business.
The dashboard will also allow the metrics to be roll up to Figure 3, by Line of business. Figure 6 shows the P&L to net profit. The operations is the consolidation of Figure 5.
Figure 6. Profitability analysis based on long term strategies by Market segment and Line of business
Conclusion
The operations dashboard will analyse decisions made by market segment and line of business to mitigate short term risks in the operating divisions using profitability analysis. The dashboard will be able to identify all items related to the goods & services provided to the customer and analyse of the mix of market segment and line of business.
The further analysis below will add further depth into the dashboard to be a management reporting system.
Further Analysis
1. Cost analysis - Cost allocation
- Shared and dedicated cost
- Incremental and fixed costs
- Capacity Costing
- Cost recovery of capital expenditure
2. Key performance indicator analysis
- Revenue units
- Costs units
3. Budget, Target and Forecast analysis - 5, 10 year plans
- Annual budgets
- Quarterly, monthly, weekly
4. Historical analysis
- Business Plan
- Year to Year
- Quarter to Quarter
5. Strategic analysis
- Long term
- Short term
- OPEX vs CAPEX
A blogger writing about data analytics. Where to begin? I start researching the subject that has come so easily to me in life. Why do I like working in data analytics? After many false starts, I came across the “Did you know?” series on YouTube. There are many versions and different themes. The first, “The progression of information technology” researched by Karl Fisch and the second by AndromedasWake’s Channel.
Now after looking at that with eyes and mouth open with the pumping beat in the background, let’s take a breath and look at what we found out in the last 5 minutes. (Additional information has been updated from teachertube, Social media revolution)
The People
China total population 1,300,000,000.(Imagine an auditorium with 1300 people and then imagine another 1 million of these auditoriums )
US total population less than India – 25% population with the highest IQ’s
Technical information doubling every 2 years
Today learner will have 10-14 jobs by the time they reach 38yrs old
¼ people employed < 1 year
½ people employed < 5 yrs
2010 - top 10 jobs did not exists in 2004
1/8 married couples in the US met online
In the last 5 minutes, US – 67 babies, China – 274 babies, India – 395 babies
The world is changing as it should. We won’t be able to say to our children “What do you want to be when you grow up?” And the first touch with our life partner may be over cyberspace and not in person.
The Technology Text Messages
1992 - First sent
Today - Sent everyday exceeds the population of the planet
Google searches 2006 – 2.7 billion a month
Today – 31 billion
Years to reach 50 million Radio - 38 years
TV - 13 years
Internet - 4 years
iPod - 3 years
FB - less than 9 months (100 million users)
iPod apps - 9 months (1 billion hits)
FB a country it would be 4th largest between the US and Indonesia but China Qzone larger with over 300 million using there services
Internet devices
1984 - 1,000(Remember where you were and what type of computer you were using) 1992 - 1,000,000
2008 - 1,000,000,000
Data transfer – 14 trillions (short – 10^12, long – 10^18) bits per second
CD’s = 2,660 per second
Phone calls = 210 million per second
2013 – computer with the computational power of human brain
2049 – computer with the computational power of the entire human species
In the last 5 minutes, 694,000 songs downloaded illegally(I can honestly say I have never downloaded a song illegally )
Technology has made us find different ways of reaching out to more and more people in a shorter time. We no longer have to wait for the news, the news now comes to us. I did not know about MJ’s death until well into the late afternoon when we knew in the early morning. So goes to show if you do turn everything off you may never know but you will eventually find out using one of the mediums, it was FB.
The Knowledge Words – 540,000 (English language)
5x more than in Shakespeare’s time
New York Times – one week is more than information than a lifetime in the 18th century.
Unique information this year 4 exabytes (4×10^19) will be more than the previous 5,000 years.
Wikipedia – 13 million articles
New articles - 156.23 per hour
Blogs – 2,000,000,000(Can you hear me?) 54% post content or tweet daily
The people and the technology have given us an amazing knowledge base. Everybody wants to share information, even me! ( makes you wonder what did all the ADD people do before the internet?)
Whether or not you believe the numbers is a totally different question (and won’t be discussed in this forum). What we have done here is all to do with the numbers. We are comparing where we are now to where we once were. Another title for this series is called “Shift Happens”. We are comparing our population change, our technology growth, our extensive knowledge and how we transfer this knowledge all around the world. The numbers show that we have been able to achieve so much in such a short time and the ability to achieve so much more.
The AndromedasWake’s version of Did you know? This one made me think about the variances we have in our numbers.(The last 1min 15secs are pretty pictures)
The Universe Age – aprrox. 13.7 billion years
Size – expands 93 billion light years, 3 dimensions - it has no edge or centre, Matter & energy - less than 5% is detectable(What is the other 95%?),100 billion galaxies, septillions(short, 10^24, long, 10^42, so many zeros , doesn’t matter which scale)of stars Birth – can be reckoned to 10 tredecillionths(short, 10^42 or long, 10^72)of a second before time began(Can we fathom that amount of time?) No one knows what happen prior to this time(nothing to measure )
The Knowledge Sun – light generated takes 10,000 years to reach the surface from the centre.
Exoplanet - twice the size of Jupiter and orbits its sun in 3.2 earth days.(All 4 seasons in 3.2 days) Shooting stars – millions occur everyday
Neutron star – rotates at 716 times per second, the equator surface achieving 24% the speed of light
Gammar ray burst – releases as much energy in a few seconds than the sun in it’s lifetime
Milkyway – 15 satellite galaxies orbiting
Venus – one day is longer than its year
Saturn – density is so low, the entire planet would float on water
Pluto – water ice is harder than steel
In contrast to the first Did you know, no thump, thump, thump in the background. And also the contrast in the numbers and how much we don’t know. We only know what we can measure and compare to what is known here and now.
Imagine the time light being generated from the sun’s centre today and reaches the surface. What amount of knowledge will we have accumulated? Will we be able to harness all that energy out there? Will we be able to transmit as much data as an exoplanet’s orbit or a neutron star’s rotatation? Will we have the answer to the Before Time question? Too many questions, known and unknown, to be asked .
The numbers I deal with daily, of course, do not bring out one’s imagination as the one’s we have seen today. But, it is the numbers that reveal the questions and it also the numbers that will show our achievements. This is why I am passionate about data analytics . Yes, some call me mad but data analytics is not boring.
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