BERKSHIRE HATHAWAY TOOK A $1.1 BILLION STAKE IN APPLE SHARES. HAVE MARKETING METRICS BEATEN EXPERIENCE?

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BERKSHIRE HATHAWAY TOOK A $1.1 BILLION STAKE IN APPLE SHARES. HAVE MARKETING METRICS BEATEN EXPERIENCE?

Mr. Warren Buffett, the Oracle of Omaha and owner of Berkshire Hathaway, has for some years, traditionally stayed away from most tech companies, and even voiced his aversion to the possibility of investing in Apple or Google, because “he just doesn’t know how to value them”:

http://www.fool.com/investing/general/2015/03/31/why-doesnt-warren-buffett-own-apple-inc.aspx

But just few days ago, the news emanating from NYSE and NASDAQ finally revealed that Berkshire Hathaway purchased $1.1 billion position in Apple Inc. Has Mr Buffett, the stock guru, allowed his personal opinion to give way to evaluative metrics or is it forecasting that was at play? Probably this move may have come as a surprise to marketers and the business world owing to the fact that this deal was sealed at a time when Apple market share proportion is going down with high revenue per item. According to Andrés Cardenal of Motley Fool Stock Advisor, the three possible reasons why Mr. Buffett may have changed his mind towards Apple are Apple’s rock-solid competitive advantage, unquestionable financial advantage and possible undervalued Apple Stock:

http://www.fool.com/investing/general/2016/05/17/3-reasons-why-apple-is-a-warren-buffett-stock.aspx

“You can’t manage what you don’t measure” is an age-long marketing adage. In today’s hyper-competitive business landscape Buffett must have determined and measured the key success metrics of Apple Inc. to have agreed to have a stake in the business. According to Jim Lecinski, Managing Director of Google U.S.A Sales & Service, “Data beats opinion” (Petersen et al. 2009). So is it data or metrics that really led to this change of heart by the legendary stock guru?

https://www.google.com.au/#q=berkshire+hathaway+and+apple

Over the years measurable data and measurable metrics have revealed big prospects in the IT industry. There is no doubt that Mr. Buffett and his 3T’s (Tim Cook, Todd Combs and Ted Weschler) would have considered a repertoire of both financial and non-financial metrics using various dashboards to arrive at their decision-dashboards like customer-performance records and stakeholder-performance scorecards that track the satisfaction of various Apple actual and potential users. Customer Lifetime Value CLV (which estimates future profitability of Apple customers over their lifetimes as customers) and Share of Category Requirement SCR (which looks at what proportion of all smart phone users buy iPhone) are some of the important financial metrics that he would have considered.

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Of course short-term return on investment and long-term brand equity (which is net profit or cash flow plus improvement in marketing asset) must have played important roles together with behavioural, memory, physical activity and marketing activity metrics, customer profile and financial metrics. There is no one size that fits all when it comes to critical data needed to make important managerial decisions like this one. But greater intangible assets linked with the creation of more shareholder value is essential (Balasubramanian et al. 2005 in Amber & Roberts 2008). Mr. Buffett and Co must have carefully analysed Apple products sales data to predict growth in this market (Iacobucci 2014).

Using Bass Model of Diffusion of Innovation equation, Buffett must have calculated the future market potential of Apple;

nt = [p + q (Nt-1/M] (M-Nt-1)

Where:

nt = Sales of Apple units in period, t;

P = co-efficient of innovation;

q = coefficient of imitation;

Nt-1 = Cumulative sales of Apple units up to period, t-1; and

M = maximum possible market potential of Apple

Market forecasting is a challenging part of stock market analysis (Nedletcheva 2015); a predictor of the diffusion of innovations (Albers 2004); and an estimator of maximum sales potential (Iacobucci 2014). Although market prediction has become the most complex task of an analyst, it helps traders to choose the type of security, the time to buy or sell a security, and the amount that they should invest on that security (Nedletcheva 2015). The business world is precarious and stock markets fluctuate considerably.  For example take a look at China Mobile, the world’s largest wireless phone firm. Its share is down 28% from $75. Also Belgium-based Anheuser-Busch which owns 25% of the global guzzler market and 16 brands that sell over $1 billion each year has had a wobbly past but now the company has 3.5% dividend yield-an indication that some stocks will shine again (Fisher 2016). Buffett may be right as he’s always is!

The effectiveness of marketing evaluation is not only pivotal but fundamental to stock market valuations (Farris et al. 2006), and for forecasting the diffusion of new Apple products using Bass Model and Bass Diffusion curve which may not be as difficult owing to past experience, existing data and conjoint analysis. Do we now say that Berkshire Hathaway has correctly evaluated marketing strategies and expenditures or was the deal based on forecasts? Time will tell with the growth or decline of Apple Inc., and when the share size of its market in the IT industry is analysed. After all, according to Erv Shames, former CEO, Kraft Foods, “better metrics lead to better decisions which lead to better outcomes”.

Reference

  1. Albers, S (2004). Forecasting the Diffusion of an Innovation Prior to Launch. Wiesbaden 2004, pp. 243-258. Accessed online from http://www.forecastingsolutions.com/downloads%5CDiffusion.pdf
  2. Amber, T. & Roberts, JH. (2008). Assessing Marketing Performance: don’t settle for silver metric. Journal of Marketing Management, 2008, Volume 24, Number 7-8, pages 773-750. Western Publishers Ltd. Accessed online from http://web.b.ebscohost.com.ezproxy-b.deakin.edu.au/ehost/pdfviewer/pdfviewer?sid=d703350d-9ada-4e71-9645-3c5496ab1e00%40sessionmgr104&vid=1&hid=123
  3. Australian Marketing Institute. Metrics for marketers-A new framework for measuring the value of marketing. AMI Metrics project. Accessed online from http://www.libraries.vic.gov.au/downloads/Statewide_Marketing_Project/marketing_metrics_ami.pdf
  4. Farris, PW, Bendle, NT, Pfeifer PE & Reibstein, DJ (2006). MARKETING METRICS: 50+ METRICS EVERY EXECUTIVE SHOULD MASTER. PEARSON EDUCATION. INC. PRENTICE HALL. Accessed online from http://ptgmedia.pearsoncmg.com/images/9780131873704/samplepages/0131873709.pdf
  5. Fisher, K (2016. Why Uncertainty is Good for Stocks. FORBES 19 April 2016, Volume 197, Issue 5, page 68-68. Ip. Accessed online from http://eds.a.ebscohost.com/eds/detail/detail?vid=4&sid=5a7f6108-0c91-41dd-aa21-ec11439283a1%40sessionmgr4002&hid=4110&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#db=heh&AN=113990961
  6. Iacobucci, D. (2014). Marketing Management, 4th Accessed online via Mindtap, Cengage.
  7. Nedeltcheva, GN. (2015). Forecasting Stock Market Trends. Journal of Economic Quality Control, 2015, Volume 30, Issue 1, page 21-28. 18p. Accessed online from http://eds.a.ebscohost.com/eds/detail/detail?vid=1&sid=5a7f6108-0c91-41dd-aa21-ec11439283a1%40sessionmgr4002&hid=4110&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#db=bth&AN=103104969
  8. Petersen, JA, McAlister, L., Reibstein, DJ., Winer, RS., Kumar, V. & Atkinson, DJ (2009). Choosing the Right Metrics to Maximise Profitability and Shareholder Value. Journal of Retailing, Volume 85, Number 1, 2009, pages 95-111. Accessed online from http://pages.stern.nyu.edu/~atakos/centerresearch/metricsshareholdervalue.pdf
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