True genius resides in the capacity for evaluation of uncertain, hazardous, and conflicting information.
- Winston Churchill
The extent of pollution or absence of it, the purity, the consistency and continuity of supply, the capacity of the human body to absorb it, the value of fresh supply - the overall salubrious environment that helps a human body to stay healthy and fit, or the lack of it, and the spectrum in between. Let the analogy unfold in mind as it can and perhaps in almost all the scenarios that the mind can conceive, information in an organization is just like oxygen to a human body.
The word "information" is perhaps one of the most frequently used words in management, yet not always well-understood. Even after excluding the truly and obviously damaging variants of the social-media wave i.e., misinformation and, worse, disinformation, there are multiple other possibilities to consider, to construct an effective continuous improvement system.
The desired outcomes of a good continuous improvement culture are reflected in multitude of key indicators which, often, keep undergoing some change. In addition, continuous improvement is also ascertained through indicators not necessarily quantified but adequately palpable in the environment (such as the textures and undertones of discussions and debates). Beneath this layer of visible indicators lies the foundation of information.
There are numerous possibilities while ascertaining the quality or utility of the information available. While there are various viewpoints and academic articles related to this scope available in academic papers, this article is in the context of continuous improvement or operational excellence in business organizations. Furthermore, the constructs which propose more dimensions of visibility or availability of information are certainly more sophisticated as against the linear or unidimensional hierarchy given below, but for brevity and simplicity, I have restricted this article to this simple list. Also, I would not audaciously claim that the list below would cover all possibilities yet may capture most.
1. Information neither available nor can be made available: This is often applicable when trends are required for benchmarking for newly developed processes and no similar process existed earlier. Hence, there is no past data even in a coarse form. Response to Covid related supply chain disruptions or labour shortages were typical situations in which only the best possible efforts could be planned, but no further measurement of improvement was feasible. The only possible benchmarking was related to similar concurrent examples.
2. Information not available but can be modelled and coarsely compiled: A little better situation. The past data, though some similar process existed, is not available and benchmarking in its desired accurate form is infeasible. For example, timestamps of actual receipt of goods by customer are made electronically available through a new real-time signature-based acknowledgement process, however there is no past data to compare with. The benchmarking process has to be developed afresh and the past estimates are decided only through common perception validated through tools such as customer surveys. Similar data is however often available and can be used too to the extent that it serves the purpose of steering improvements for the future. This often paves way for increasingly improved benchmarks to be developed as the process is perfected over the initial few weeks or months.
Minutes of meetings not standardized, each supplier/customer having own different forms of reports with information not necessarily aligned across all the suppliers/customers, different bank accounts exporting spreadsheet extracts with different coding systems and comments are a few examples. Compiling and unifying such information into a meaningful database is a colossal task and it often deters improvement practitioners from taking any further steps. Instead, decisions are taken intuitively.
3. Information available and accessible but requires validation: This information is invariably manually compiled with some judgement, perception or unscientific estimation by the person observing and compiling the data. Such information often consists of opinions, observations and varying evaluations done by people through their specific viewpoints. Suppliers' or customers' or employees' demeanour, decorum and mannerisms, immeasurable performance of employees etc. Without being duly validated through blinded assessments done by multiple assessors, such information is of little value or can be even detrimental to the process utilizing it. Consistency and meaning in such cases can be built through building ratings on 1-10 scale or the Likert scale, using them with blinded inputs and establishing a pattern over time by miniaturizing it. (For example, "Please highlight why your rating for effective facilitation increased from 6/10 to 8/10 this week. Your remark last week was "no action follow-up" associated with the score 6/10.") Sampling also can be systematically used to make the information meaningful.
4. Information available, accessible, and reliable but requires finishing or additional analysis or remodelling before application: This is typically the data that is compiled in generic form such as a well-organized database consisting of headers and records with unique attributes and encoding schemes complying with the data-modelling conventions. It is only interpreted for summary presentation as required by the unique decision-making processes. All the raw data systematically collected through well-structured forms inputted into well suited software would fall in this category.
5. Information available, accessible, and useful as provided - requires only decision-making: This is truly the information that users need for decision making. No further processing or presentation is required. Typical business intelligence utilities incorporating the visual and the data elements along with the scalability and flexibility for any investigation as required fall in this class.
6. Useful information is available and automatically used for the applications using it: This is truly the best form wherein manual intervention is often not even required. The feedback loop ensures that the information automatically generates the action that needs to be triggered on the basis of that information. For example, a completely automated e-Kanban, wherein the threshold level of the residual stock of a commodity in the supermarket store leads to generation of a new replenishment order which signals the warehouse with availability, to dispatch the quantity required.
The heart of the matter
The value proposition in any CI/OE programme is always to increasingly enhance the value delivered chiefly to customers and the shareholders and, the other stakeholders of the business such as employees, suppliers, and government or society at large. Such value proposition entails continually changing demand for information. For a continuous improvement facilitator what truly matters is how the target audience moves from the lower level of information they use to the next higher. Needless to mention that when the system really matures - it's time for some new features too. So, the continuous improvement never stops! (That's a tautology anyway.)
A report that gives "Delivery on Time" as percentage of orders fulfilled in time soon requires that to be classified by season, within season by geographic zones, within zones by periods when the Covid incidence peaked or subsided, and by product - and by discount segment by product - and by the duration of promotion scheme - and - the list does not end.
A dream for "the one, final and perfect state" of the availability of information is a utopia. Data is where it all starts but does not end there.
As Claude Elwood Shannon aptly said,
"Information is the resolution of uncertainty".
With change being the only true constant in business, uncertainty never ends. However, with effective information, it can be resolved effectively.
- Nilesh Pandit
22nd December 2022