Why are some firms more competitive than others? This is the central question of my research in the field of strategic management. Decades of research, in both the life sciences and other industries, have converged to suggest there are perhaps three overarching reasons.
The first is the most obvious: what academics call the ‘Resource-Based View of the Firm’ (RBV for short) says that firms’ advantages come from their distinctive assets. These might be tangible, like R&D facilities or cash reserves; or they may be intangible, like intellectual property or brand reputation. The second reason builds on RBV with the idea that sustained competitive advantage flows from firms distinctive capabilities.
Capabilities can be anywhere in the value chain from discovery to marketing but, to be distinctive, they must be superior to those of your peers. Taken together, resources and capabilities explain most success stories. Today’s exemplar companies, such as Gilead in pharma or Medtronic in medical technology, are good illustrations of resources in R&D and capabilities in marketing.
However, there’s an important problem with these first two explanations of competitive advantage. Both are built on the premise of strategic alignment, meaning that firms succeed when what they do matches the market environment. Gilead’s success stems largely from aligning to the rise of viral diseases, like HIV and Hepatitis, as important disease categories.
Medtronic’s success can be seen as aligning to the rise of electronic stimulation as an emergent technology. In other words, both RBV and the distinctive capability-based school of thought are about aligning to the market. Therein lies the problem. When the market is changing, as it is today any market alignment is only temporary and even firms with fabulous resources and outstanding capabilities can fail. The history of our industry is littered with once-great firms which lost alignment as the market changed.
To understand success in changing markets, we need the third reason. This is the dynamic capabilities perspective, which explains long term success as the ability to adapt and reconfigure resources and capabilities to changing market conditions.
What is Organisational Learning?
Organisational learning is the acquisition of new knowledge by the organisation. This seems a statement of the obvious until one defines what it is not. Organisational learning is not the acquisition of data or even of information; it is when your company learns, for the first time, how something is caused, how something works or what something is.
For example, how markets really segment, how a market access decision is made or what a compelling value proposition looks like. Nor is organisational learning an individual or even team activity; it is when that new knowledge is embedded into the organisation (so that it is not lost when personnel change) and can be commercially exploited.
Finally, organisational learning is not the acquisition of obvious knowledge that every competitor can gain without difficulty; it is the attainment of intelligence that competitors could not easily acquire or copy.So, for example, a firm that acquires lists of Key Opinion Leaders (KOLs) is not really learning; any competitor can imitate that easily.
But a firm that acquires that list along with an understanding of where those opinion leaders fit into the market’s decision making processes is beginning to learn; and the firm that understands what that knowledge implies for the structure and capabilities of its sales team is truly learning.
Two Ways to Learn
If organisational learning is not simply data collection and is critically important in changing markets, then an obvious question arises:
How can our firm learn faster and better than our strategic rivals?
My research and that of many earlier workers suggests that there are really only two ways: buy or make.
Life science firms buy knowledge all the time. If I want to buy knowledge about how the respiratory market works, I might buy, partner with or out-license to another firm already strong in that disease area. That is what Almirall did recently when it sold its respiratory business to AstraZeneca. If I want to buy knowledge about antibiotic resistance, I might in-license or acquire a specialist firm. That is what Merck did recently.
Buying knowledge is quick, but there are many reasons why it is not always the best option.
Firstly, you might not know what knowledge you need to buy.
Secondly, the knowledge you need may not be available anywhere.
Thirdly, if it is available and it is valuable, you will pay heavily for it.
A fourth reason is that bought knowledge is rarely unique; if I pay a consultant or contractor for knowledge, it is unlikely I am their only customer.
Finally, it may not be very easy to assimilate and act on the knowledge, such as when clients fail to act on the market research they have bought. For these and other reasons, a firm may decide not to buy its knowledge but to make its own.
Starting From Somewhere
My research into how life science firms are evolving reveals many examples of organisational learning. How branding influences pricing in emerging markets, how payers use prescriber’s advice and how to create value beyond the product are three examples.
But, in all of the examples of excellent organisational learning I have uncovered, there is one common denominator: we start with an opinion. We might, for example, think we know who would be involved if our customer had to reshape their patient pathway to use our product.
We might work on the assumption that the decision making process for our new primary care product is the same as for our existing products. We might feel confident that the first adopters of our new diagnostic test will be a certain innovative target segment.
Whether the existing “knowledge” is fact-based or an opinion, whether it comes from experience or from research, we rarely address a business situation without some level of existing knowledge about the situation. Knowledge creation is rarely “ab initio” and is almost always about improving the validity and value of our existing knowledge or opinions. It is this insight, originally developed by the great US researchers Agyris and Schon, that allows us to understand how firms create the actionable knowledge that leads to competitive advantage.
The Learning Loop
Agyris and Schon realised that firms transformed weak, invalid knowledge into strong, actionable insight through a learning loop. In essence, the loop has five stages, as shown in Figure 1.
In my work, I have learned that, although simple in principle, there are important, real-world lessons that we can learn from exemplary companies about implementing the loop.
The first step in the learning loop is to list all of the major activities you either have planned or are currently executing. For example, this might include a KOL campaign, a health economics comparative study vs. another brand or a shift to Key Account Management programme. The practical lesson to note is that all significant resource-consuming projects should be identified because each one indicates where you are operating with some existing knowledge or opinion.
The next step is to identify the one or two underlying assumptions upon which each activity is predicated. In our examples, these would be that KOLs drive sales, that the customer-perceived comparator is the other brand, or that product choice in big accounts is centrally directed. Typically, these assumptions are implicit, and exemplary companies work hard to make them explicit.
The third step is to develop hypotheses based on these underlying assumptions. In our examples, good hypotheses would be that our sales should be strong in the area where the KOL is favourable to us; new usage in our disease area is the comparator brand; and that key accounts concentrate their purchases onto one brand. Best practice in this important step is to ensure that the hypotheses are testable with unequivocal results.
The penultimate step is to test the hypotheses using real data. In our examples, we would look for correlation between local market share and KOL attitude, for usage patterns in new prescriptions, and for share distribution within major accounts. Our most interesting finding here is that many firms may collect the right data to test their hypotheses but their information systems are often set up to support management control and not organisational learning.
The final step in the learning loop is to revise your assumptions in light of the tests. Sometimes, prior assumptions are supported, but in our three examples (all taken from real cases) they were not. These cases revealed that KOLs were not very influential, that the customer-perceived comparator was not the competitor brand but a generic, and that many key accounts had such uncoordinated purchasing systems that they should not be treated as key accounts. These cases also revealed that important lessons, even when evidenced by data, were often hard for executives to swallow.
About the Author
Brian D Smith is a world-recognised authority on competitive strategy in the pharmaceutical and medical technology sectors. He researches the evolution of the sector at the University of Hertfordshire, UK and SDA Bocconi, Italy.
