Information Technology: Commodity or Strategic Resource? (1)

Posted on 24. may, 2010 by in Information Technology, Operational Excellence and Strategy & Innovation

united-kingdom-over13A few years ago, a paper in the Harvard Business Review raised a heated controversy.  It was titled “IT Doesn’t Matter”.   The basic tenet of the author was intriguing: IT has become a commodity, “affordable and accessible to everyone, it no longer offers strategic value to anyone … Now that IT is ubiquitous, we must focus on its risks more than its potential strategic advantages … But the greatest IT risk is overspending … The lesson: make IT management boring.  Instead of aggressively seeking an edge through IT, manage IT costs and risks with a frugal hand and pragmatic eye.”  With IT accounting for 40% to 80% of companies´ capital expenditures, over-investing (capex) and overspending (opex) is certainly worrying.  Put that in the context of a global economic contraction, and it is even more disturbing.   But, is it wise to center IT management on its costs and risks and forget about its potential value?   In this post and the next, I will explore the business value of IT (BVIT), its sources, and its implications on IT management.

IT management deals with both the technology and its content.   Storage, processing and communication are what the technology is all about.   Content is a bit more subtle.  Data, information, knowledge, and intelligence are associated to distinct maturity steps.   Less mature firms deal only with data, symbolic representations of facts and transactions.  More experienced firms are able to create information out of data.  Information has meaning to a decision maker in a business context.  Information is valuable because it reduces uncertainty.   Repeated use of information by decision makers in an action-learning environment creates knowledge, in the form of models which map situations to decisions.   Knowledge occurs within human minds, although firms do attempt to codify it through business policies and knowledge representation systems.   Intelligence implies the use of knowledge to transform the organizational and business context in the direction of purpose (business objectives).  Data and information are closer to the technological means, whereas knowledge and intelligence are much closer to the human being and its social, economic and political context.  Some people propose a fifth maturity step: wisdom.   A colleague at a university’s decision science department, where I worked for almost twenty years, used to say that knowledgeable people accumulates know-how, whereas wise people go beyond; they develop know-when, know-where, and know-why.  I still like that perspective.

Business value of IT (technology + content) centers on three key roles it plays in firms: a) support decision processes, b) automate and coordinate internal business processes and c) automate and coordinate inter-organizational business process, interacting with markets and partners.   In this post, let’s explore IT value supporting decision processes.

IT gap and decision quality:  when a manager faces a decision, she typically goes through four steps: exploration, identification & modeling, solution and implementation.  The situation is explored to understand problems and/or opportunities.  Once the key issue is identified, a model describes the objective function (for ex. minimize costs), key variables involved and their relationships (cause and effect, feedback), constraints, uncertainties and scenarios.   The solution space, constituted by all possible solutions to the problem, is explored to determine the optimal (or satisfactory) candidate solution(s).   Once a solution is selected, the decision has been made and implementation follows.

Quality of a decision depends on many factors.  In theory, if all variables and constraints have been considered, the optimal solution is the one with the highest quality because it optimized the objective function.  In business practice, however, many real-world variables and relationships cannot be properly modeled.   Moreover, business decision makers may be rational but their rationality is bounded by limitations in time, resources, information and cognitive ability.  Satisfactory (good enough) solutions are often chosen and implemented.  The decision process is not linear, and the decision maker iterates between exploration, identification, solution and implementation.  This action-learning creates knowledge.   New variables are considered, models are refined, new uncertainties identified, and sensibility analysis and “what if” explorations incorporated … and decision quality improves.   This is an information-hungry process. When an organization does not provide key information support to its decision makers, decision quality suffers and organizational learning and knowledge creation is hindered.  Information support should include relevant information, but also decision modeling and solution systems, often called decision support systems.

Poor decision quality diminishes effectiveness and efficiency.    The organization might pursue the wrong objectives with the wrong resource allocation.

IT gap, excess uncertainty and behavioral variations in resource allocation: Let’s talk about a particular but usual case of poor decision quality, one which is rooted in human behavior and self interest.  Consider a manager that has established a decision making model for allocating resources in his area, but faces excess uncertainty.  I am not talking about natural uncertainty associated to unknown factors and events.   I refer to an information gap, available data in the company that has not been converted to information and timely delivered to decision makers.   The manager faces a dilemma.  Should he be “conservative” or “liberal” when allocating resources?

Consider the case of a new promotion that is about to be launched and the distribution manager faces huge uncertainty regarding demand.  What are the appropriate inventory levels?   If he opts for conservatism and the promotion is wildly successful, an opportunity costs will be incurred, sales will be lost and customers will be confused with the mismatch between promotion and availability.  A big personal risk of under-allocation is visibility: the manager responsible for the undesirable effects is easily identified and make accountable.  If he opts for a liberal inventory policy and the promotion is not very successful, inventory costs will be elevated, but he could easily argue that responsibility lies with sales and marketing and its failed promotion campaign.

Over-allocation is much more prevalent than under-allocation, and this creates large amount of slack resources (Oswaldo calls them cushion resources).   Here are some typical examples:

  • Cash: a treasurer faces excess uncertainty regarding in and out cash flows. He plays safe and builds excess cash. This is an asset slack with a financial cost (interest paid, or interest not earned)
  • Inventory: an inventory manager has excess uncertainty regarding demand and supply. Last time she ran a tight inventory, sales were lost in territory xyz and she was held accountable. She decides to put together a few layers of extra inventory just in case. Again, this is an asset slack that requires additional working capital and entails a financial cost. Notice that slack inventories could occur in raw materials, work in progress and final products.
  • Plant and equipment: an operations manager faces an information gap regarding the impact of future sales and marketing efforts on production capacity. He has underestimated demand in the past and has taken the heat of insufficient capacity. This time, he builds extra capacity. The asset slack reduces asset turnover and profitability. An IT manager at a retail bank does not have access to good projections of future customer transactions, which are expected to expand as a result of new branches and product introductions. She decides to overestimate IT processing, storage and communication capacity; hence IT capex and future opex are inflated.
  • Human Resources: the underwriting manager at an insurance company aggressively recruited personnel last year to accommodate for expanding demand from a new successful product. Recruitment continued even when demand started to moderate. A year later, she thinks it would have been more appropriate to have built a mix of permanent and temporary workers, instead of the overextended workforce she now has in the payroll. Fixed costs have increased, but it is too late because the base country of this operation has a very restricted labor market.

We could go on and on, but the conclusion is the same.   An information gap produces excess uncertainty.   Managers sometimes underestimate resources and assets, performance gaps result and those managers are held accountable.  In my experience, seasoned managers learn that it is better (for them, not for the company) to respond to an information gap by overestimating resources and assets (cash, inventories, fixed assets, staff and so on).  Slack resources are not always easily identified and linked to management decisions, unless the company has a great cost management capability.   In any case, it is always possible to attribute overestimation to uncertainty.  But our key point is that uncertainty has two components: natural uncertainty inherent to unpredictable factors and events, and excess uncertainty resulting from information available to the company but unavailable to the decision maker.   It could be a fact that already happened, a projection in a functional area that affects another function.  In any case, the company was unable to timely deliver relevant information to the person in charge of setting direction and allocating resources.    If this happens frequently to the top 20 (or 200) decision makers, this company has a big efficiency problem.  Its cost structure will get fatter, not because there is a premium value added to customers and other key stakeholders, but because the company lacks information capital.   Over the years, this inefficiency could accumulate and create a serious competitive disadvantage.   On the other hand, the competitor with a superior strategic capability identifying information needs and delivering it to its key decision makers will enjoy a competitive advantage.

In conclusion, a key business value of IT is to improve decision quality and reduce slack resources.  If a company develops a superior strategic capability for supporting managers with the information and systems they need to make better decisions, it will improve efficiency and effectiveness.   Not only it will have a leaner cost structure aligning slack resources to natural uncertainty (efficiency); it will do a better job of identifying and improving key levers of business performance (effectiveness).

Of course, this does not mean any IT investment aimed to improved decision support technology and information will create economic value.    Sound IT management directs such investment to those initiatives with a positive business case.   A good starting point is to create a decision map for the business and identify critical decisions, those with the greatest sensitivity to financial and strategic goals.  These are the leverage points for investments, where small improvements in decision quality create greater value for fundamental stakeholders.

In the next posts, we will comment on business value of IT associated to internal and inter-organizational business processes, as well as the implications on IT management.

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One Response to “Information Technology: Commodity or Strategic Resource? (1)”

  1. Clare Mccormick

    28. may, 2010

    You’ve done it once more! Incredible read!