Big Data: 3 insights from Baseball [video]

I recently saw again the film “Moneyball” by Bennet Miller of 2011, based on the book by Michael LewisMoneyball: The Art of Winning an Unfair Game”. It tells the story of the baseball team Oakland Athletics and of Billy Beane, their general Manager in the years 2001 and 2002.

I felt like someone watching something that “doesn’t say, but enlightens immediately”, these two topics occurred to me: Big Data and Change Management.

Nothing like the storytelling of a real experience can be as effective. The story of the film throws a light on the situation that many organizations are presently experiencing: give value to business through Big Data.

Back in 2001/2002, the technologies of Big Data and relative Analytics as we know them today, were not yet available. But what Billy Beane sensed and then realized contains business analysis models, management of Big Data and above all a coherent plan of change management necessary to extract value from the data.

In the 2001 season, the Oakland Athletics are defeated by the New York Yankees. The possibility of entering the World Series is vanished. As a consequence the General Manager is denied a budget increase to buy new players for the new season. The situation is made worse as three champions are leaving because their contract has expired. Negotiations to buy new players will be difficult. The Scout team (the people who are responsible for identifying the players to buy, in line with the budget and the game strategy) is under pressure from the General Manager.

During a negotiation with the Cleveland Indians, Billy Beane meets Peter Brand, a young Yale economics graduate, at his first job with Cliveland. Peter has his own personal vision regarding Baseball, but the Cleveland Managers do not listen to him.

Bily Beane, though, percieves something genuine and urges Peter to explain his approach to basebal through the models of the mathematician Bill James. Billy Beane is impressed and hires Peter to work with him in the Oakland Athletics team.

“Right” questions and going straight to the point…

Peter gathers statistics and writes software to identify the best indexes for the approach he follows, finding a list of potential players to carry out the strategy shared with Billy Beane.

Presently, after a 10 year span, Big Data Economy is bursting forth. Every item can produce a great amount of data. Our own selves, through our personal devices, credit cards, automobiles, watches produce a series of data that reveal habits, preferences, etcetera. Healthcare, Finance, Logistics, Retail, Marketing, Automotive are only some of the business areas in which Big Data are used. Crucial factors such as computing power, huge storage capacity and data access, everything becomes measurable and available.

But a competitive advantage can be reached without these factors. The film, as a matter of fact, shows the value lying in the understanding and in the ability to grasp the significance in the Big Data. At one condition, however. That the right questions are asked to fully understand the phenomena and the business.

Peter, as a matter of fact, focuses on how to gain victories, not on which players to buy. He has gone to the heart of the baseball game (the business). Only with the right number of runs you gain the necessary innings and victories and you can win the championship. If you concentrate on the players, you risk evaluations of factors that are not directly related to the aim “number of victories”.

The complexity that nowadays Big Data provide regarding current business phenomena fare exceeds this – even though brilliant – Baseball interpretation. The same way as the Cleveland Indians Management did not realize the value of Peter Brand’s analysis model, are we sure we grasp the correct meaning that Big Data are currently giving us regarding phenomena caused by model changes that technology brings about in many businesses?

The risk is to question data with the aim of looking for a linear progression trend if there really isn’t a new interpretation model.

and then how do we bring change about?

Business knowledge and the “right” questions are not enough. At the beginning of the championship the Oakland Athletics suffered a series of losses. The press mocked their General Manager, accusing him of following weird mathematic formulas, the Scout team criticizes his refusal to use their experience and their “human touch”. Even the Coach doesn’t follow his instructions on the players to send on the field and on the game strategies.

Without immediate successful results, all organizations refuse the introduction of innovation, in this case the introduction of new metrics. Tension runs high with the Oakland Athletics. Billy Beane is under siege. The clash with the Scout Manager leads to the exoneration of the latter. However, Beane does not give up and follows his strategy through constant actions aimed at carrying out his plans. He faces the Coach imposing the names of the players to send on the field, and when he sees his instructions remain unattended he decides to transfer to other teams several players, even if they are among the most famous ones.

At that point even the Coach has no choice left. The team on the field is the one whose potential lies in the analysis and indicators of young Peter Brand.

The General Manager has carried out his strategy through coherent Change Management actions, even tough ones.

These actions have averted two risks.

The first one is the risk of seeking confirmation. Very often, organizations undergoing strong changes struggle to judge them with indicators that are different from the past. They measure assets, competences, know how on the basis of previous success. For this reason they don’t get to appreciate the value the change brings, or may bring about.

The second risk is not changing really one’s structures and their relative assignment of responsibility and authority. Maintaining processes and roles responsible for decisions, investments and results is not coherent with the disruptive strategy that the use of Big Data requires. This risk is highly frequent at present, a time when the organizations pursuing the so called Digital Transformations are many.

Big Data… where they are useful

Digital Transformation creates change dynamics in organizations that result in the need for a wide autonomy and assumption of responsibility.

Cascading processes are ineffective, highly concentrated on the protection and control of messages to send out, but little effective in listening, knowing and involving people. Also the new Digital Manager roles are ineffective if they do not activate transversal and participated processes through a new leadership. Special or strategic projects are ineffective if they still use the classical sequential stages at the expense of interactivity required by the Digital themes.

In the film we see another change, perhaps not so obvious, but crucial for extracting value from the use of Big Data and related metrics. Billy Beane and Peter Brand begin sharing with the single players the statistics of their performance and the related characteristics, pointing out precisely the strikes/moves they can count on. Each player is thus more aware and more focused when on the field, and can interpreter correctly every moment of the game.

Big Data are useful for those who can use them to direct decisions autonomously and in a responsible way and to improve performance and results. The more metrics and their underlying models and strategies are spread in organizations, the more people add value by using their own decision-making autonomy. This is a pre-condition, that is to say give the “responsible for an area of action” (I think we will be using the notion of role less and less) the possibility to question and interpret data.

As brilliantly stated by many speakers at the SAS Forum 2015, at present, the highlight of Big Data is to create products that can win the “last mile challenge”. This was represented clearly by Pierre Philippe Mathieu, Earth Observation scientist, Applications & Future Technologies Department for ESA, when he stressed the need to change the huge amount of data presently available into small data to create business. Among the recent innovations shown and derived from Big Data, the application in the field of weather forecast is emblematic; it gives the possibility to give the farmer, via text message (precisely the last mile), suggestions on which is the best time for the rice harvest.

Conclusions

The story of the Oakland Athletics has given me three insights with regard to Big Data and how to gain value from their application in organizations.

  1. The use of Big Data requires a new interpretation skill, guided by the knowledge of the specific business area in which we operate, but guided also by new thought patterns; there is a need for new questions, that “go right to the point”, and that lead to actions that generate value in specific moments of interaction with the stakeholders involved;
  2. New interpretation models of Big Data must be implemented in the organizations, which must acquire them; too often we witness the celebration of organizational innovations ascribed to the usual “roles”, those who show command & control leadership; but at present discontinuity is such to impose new actors who have competences that are not necessarily present in the organization, but above all there is a need for a new leadership capable of creating the necessary conditions for change;
  3. Technology has enhanced many of our abilities and skills; roles that in the past were considered operational, are now characterized by a greater degree of autonomy (evaluation and decision also through the use of Big Data) and empowerment; it is through the very action of autonomy and responsible control that organization can spread a new potential and create more value; organizations can grant themselves this value surplus providing each level with tools to exert autonomy coherently with the strategic goals; the traditional ways of communication and government are open to more modern tools based on coherent data with an idea of knowledge worker capable of giving a distinctive contribution.

One thought on “Big Data: 3 insights from Baseball [video]

  1. Roberto – great post! Lately, we’ve been discussing how to make the most of big data. Your comments about how organizations can gain value from big data are very valid and worth consideration for every B2B sales manager. Thanks for your work.

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