Data management means better timing and an understanding of the wider system

Barb ClearyAs World Quality Month celebrations are replaced with attention to holiday celebrations and November’s focus fades into the distant past, facing a new year in the darkness of December may represent an opportunity to pay attention to issues related to developing and managing technology and contemplating the future of a company or organization.

Last month’s issue of Harvard Business Review, with a cover story related to “What really keeps CEOs awake at night,” addressed the timing of innovative technologies in an article authored by Ron Adner and Rahul Kapoor (https://hbr.org/2016/11/right-tech-wrong-time). We all know of technological innovations that have been released too late and missed the revolution (the article cites Blockbuster’s failure to address the shift from rentals to streaming, for example), as well as those that have been ready too soon, falling into a market that does not perceive their value.

To avoid the “right tech, wrong time” scenario, Adner and Kapoor suggest looking more closely at the ecosystems that support technologies. Understanding the competition between the new and the old ecosystems can help to assure more accurate predictions about the timing of transitions, and to render decisions about allocating resources more effective.

While the HBR article addressed the development and release of technology, the same approach may be relevant to adoption of new technology and the introduction of new features or products as well. Thinking of what were considered whiz-bang features in computers in the 1980s and recalling all the revisions in technology since then makes one’s head spin. As the technology increased in sophistication, many companies missed the mark; their names are no longer on the tongues of those who once delighted in them. Adner and Kapoor might say that they failed to understand the ecosystems into which they released their products.

So how does one understand this ecosystem and respond to it with legitimate flexibility, not knee-jerk reactions?

Keeping one’s eyes open means far more than working on product development. It may mean continuous data monitoring and analysis of factors that contribute to supportive ecosystems, even when these seem external or irrelevant. These may include:

  • Customer data
  • Development costs
  • ROI figures
  • Employee training
  • Supplier metrics
  • Current events
  • Market analysis
  • Employment figures
  • Developments in legal issues
  • Changes in tax codes

Watching the changing market for a product or service, for example, could be as simple as looking at industry stocks over a period of time—a practice that may support not only technology decisions, but also choices about product release or development.  Seeing a chart of plunging share prices for companies in a given industry gives immediate access to an understanding of how that industry may be changing; did video services’ share prices give any clue about a growing interest in streaming? It may have. Information about decreasing use of land-based phone service may chart the future for an alternative product. A chart of long term year-over-year holiday candy sales can enlighten decisions about how much to produce or whether to launch a new product line. Keeping track of customer preferences garnered through sales calls or help services may offer an advantage in making decisions about future investments and features to include in a product upgrade.

W. Edwards Deming’s idea of a “virtuous cycle” along with his suggestion that we strive to provide “jobs and more jobs,” can guide our thinking. A company should pay attention to wider trends in its ecosystems. These activities clearly can come into conflict with a focus on short-term profits. However, if providing jobs over the long term is part of a shared vision, the value of “paying attention” should become more apparent over time.

Keeping an eye on emerging trends involves more than an occasional glance at the business page in a daily newspaper. Here we can learn something from the workflow and thinking used in control charts. A control chart is a methodical way to pay attention to something over time. Sample the data, plot it on a chart, then think about the nature of changes shown on the chart. The suggestion here is not to use control charts to monitor trends but rather that an ongoing, deliberate approach to paying attention to your products, customers, services and the world they operate in should be in place. Too often, we see a customer survey done years ago held up as evidence that we should make this or that decision. Looking at important data over long periods of time in a systematic way invites the opportunity to really know the water in which an organization swims.

Pillars of traditional management, which include focusing on cost cutting and revenue growth to create short term growth, will not alone keep a company in business over the long term. It is instead a robust and agile ability to respond to changes that affect its viability. Responding to these changes means anticipating them, and this is possible only with genuine study and data collection over a period of years, not days or weeks.

This flexible and enlightened study of an organization’s ecosystem is what might be considered genuine innovation.

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