Kenya Airways’ #ticker:KQ turbulent times have forced her to attempt manoeuvres to restore her financials to good standing.
These approaches range from disposing several planes, leasing others out, staff rationalisation, all geared towards a leaner outfit. Route reschedules and cancellations are, however, the hallmark for anyone travelling on KQ as it’s commonly known.
The results have not fully yielded anticipated outcomes, but at least the previous losses are dwindling. Hopefully, KQ arrives at her target soon and flies on the former high returns for investors.
A casual observation of KQs attempts offers lessons to struggling county and private health entities. At the core of all this turnaround strategy is Big Data analysis and it’s use in making painful, but necessary decisions, especially during the ongoing uncertain business environment.
Commercial aviation has got to be one of the most data consumptive industry. Beginning with getting clients to choose your airline, advertisement placement, bookings, cancellations, reschedules and connection flights, all rely on data.
The most unpleasant result is flight bundling: overbooking clients to optimise routes. Do two planes fly half-empty or does a delay “occur” to ensure only one full flight? Are some passengers “sold” to affiliate airlines at a concession and sacrifice a potential full earning if the return flight is not fully booked?
The positive side for KQ in all the passenger inconveniences is that flight capacity increases. It also helps that such behaviours are universal among airlines, so passengers have nowhere to run.
Another observation is landings, whose timings appear to be synchronised, a well choreographed relay, one after another, oftentimes minutes apart. The same holds for departures.
Perhaps this informs staff rationalisation: fewer workers working full capacity for brief periods at half normal rates, saves money.
KQs labour disputes notwithstanding, a few lessons could be gained by health entrepreneurs during this turbulent liquidity year.
To stay afloat, reorganisations will have to occur, especially with NHIF, the largest insurer declaring loses and other insurers sounding warning alarms on the same.
The second lesson is that sharing is good. Rather than a unit operating at half capacity and needing full staffing, consider temporarily shifting this demand externally.
Thirdly, schedule facility visits to avoid staff redundancy. Here, hospitals have long periods of no activity followed by brief periods of high volume.
Analysis shows majority of such visits are not emergencies yet are unscheduled. Functional user flow dynamics could borrow from aviators.
Investment in systems and tools for data analysis and evaluation of key performance metrics is important. This is the compass for your entity’s staying aloft in turbulent business weather.
However, very few hospitals see the value in investing in such systems. While expensive initially, ultimately these will be a key asset for any health enterprise. Finding a robust one is the challenge.