In a recent interview with Martha Heller, Mike Wright, the Global CIO at McKinsey & Company, shared some insights on how they manage information and knowledge of its people to bring the best of McKinsey to every client.
Mike asserts that the greatest asset of McKinsey is the knowledge of its people. While this is true for any organisation, given the fact that McKinsey has been able to do this consistently over several decades and has managed to scale knowledge management processes to 17,000 consultants spread across 66 countries, there are several best practices that we can learn from this interview.
Use technology to augment the power of human curation
At Contify, we interact with different kinds of companies who are interested in understanding what an AI-enabled market and competitive intelligence platform can do for them. Every once in a while, we come across customers who harbour the notion that AI will somehow magically reveal some game-changing insight that no one thought about.
That’s because, even before this COVID-19 pandemic, we have been living in an ‘AI misinformation epidemic’ with widespread media coverage fuelling debate over its potential impact on business and society at large. We also tend to focus more on the ‘next big thing’ that will revolutionise the world as we know it, rather than appreciating the incremental improvements that have brought us here in the first place.
Mike says that at McKinsey, “we use AI and machine learning technology to bolster our cognitive capabilities.” The objective being to provide users with “better curation and search”.
According to Mike, we should use artificial intelligence, machine learning and other tools to augment the power of human curation. This is one of our founding principles at Contify. This article elaborates on how Contify leverages artificial intelligence (AI) and machine learning technologies to drive market and competitive intelligence programmes for our customers.
Tag information for search and retrieval
Mike said that in McKinsey’s knowledge repository, data is held in relational and graph databases with very good tagging and semantic search capabilities. “When you don’t get the answers you need, it is because we have not properly codified or tagged the data.” adds Mike
In our experience of building and implementing Contify, we found that most organisations, after painstakingly collecting information from both external and internal sources, cannot find the right information, when they need it the most.
That’s because this information is not organised properly. It is scattered across the internet on different websites and in various folders across the organisation.
To organise information for our customers and to make sure that it is retrievable when needed, at Contify, we implement customised business taxonomies. We have described this at great lengths in a series of ten articles titled “The Art and Science of Taxonomy Development.”
Use APIs to connect different data sources for specific capabilities
McKinsey has moved away from the traditional ‘high-rise’ architecture where everything is centralised in massive ERP systems in favor of a ‘low-rise’ architecture with APIs and add-ins to connect different data sources and third-party apps to build specific capabilities. As Mike puts it, “The more we can pre-populate that information from other sources, the easier we can make it for people to refine it.” That is, make it easier for users to curate and enrich information.
Right from its inception, Contify has offered human-curated market and competitive intelligence as APIs for companies to integrate into their internal knowledge systems such as ERPs, CRMs or even their customer facing applications. Read our announcement on how apps can integrate intelligence on companies using Contify APIs. Very recently, we helped a predictive analytics solutions provider leverage Contify’s News Feed APIs to enrich it’s bid management software suite with updates on new business opportunities.
In this interview, Mike also shared several other insights on how McKinsey is managing the cultural changes required in IT to support a truly data-driven organisation. He presents six specific pieces of advice to drive this change. Read the full interview here.