Business Patricia Medina

Knowledge Management: A Driver of Efficiency and Innovation

How do organizations capture knowledge and use it to create value?

By: Patricia Medina

How do organizations capture knowledge and use it to create value?

Successful organizations attribute their success to several factors notably their ability to identify, collect and distribute knowledge when needed. Knowledge refers to insights and expertise and is divided into three categories: explicit, tacit, and embedded. When knowledge partners with technology, it yields powerful outcomes. Technology not only produces new tangible gadgets but also helps manage knowledge and provides strategic direction.  In the current digital era, an increasing number of companies worldwide are exploring how knowledge management can support efficiency and innovation in their business. For example, companies have created roles such as Chief Knowledge Officers and Chief Content Officers to manage the firm’s, often untapped, knowledge assets.

What is Knowledge Management?

Knowledge management (KM) is applied in many industries and consists of a set of procedures and practices aimed at identifying relevant knowledge to create value. To accomplish its role, KM relies on various disciplines: artificial intelligence, cognitive science, and document and information tools, according to Kimiz Dalkir. In addition, knowledge is divided into three categories: explicit, tacit, and embedded.

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Explicit knowledge is organized knowledge that can be articulated and codified. This type of knowledge is context independent, meaning its development is not related to individual experience. It is reproducible and carries lower value than other knowledge types. Explicit knowledge is easily searched, shared through technology, and stored in media (i.e. internet, books, files, sounds, and visuals). It is formalized by using words, codes, or scientific models.

Among the three types of knowledge, tacit knowledge is the most valuable source of knowledge according to most literature on the subject. This type of knowledge involves a person’s know-how and expertise which have not been documented or formalized. It is usually hidden given that it is unspoken and unwritten. It is developed through personal experience and is highly subjective. As a result, it is difficult to teach and, thus, not easily reproduced. The context of experiences impacts the creation of this knowledge.

The third type of knowledge, embedded knowledge, has been less examined and exists in codes of conduct, processes, products, corporate culture, ethical principles, rules, and routines. An example is drawing lessons learned from routines.

Information vs. Knowledge, Are They the Same?

“Information is free. Knowledge is not”, notes Ian Lurie, captures the difference between the two concepts. While information consists of facts, knowledge is a skill set drawn from experiences or education and practical understanding of a subject matter. In other words, information is raw data or data available as captured without being processed. Examples of raw data are user input, digital images, machine indicators, commercial transactions, and operational outputs from business processes.

Meanwhile, knowledge involves the intersection of information and the understanding of subjects that lead to valuable concepts and produce meaningful analysis. Using the concept in the graph below, imagine a person sees a traffic light turning red (information). Next, based on experience, studying the driving signals, and passing the driving test, the person realizes the context at that moment (knowledge). Then, using both, information and knowledge, the person makes the decision to stop the car (wisdom). Ultimately, information is included in knowledge.

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What Does Knowledge Management Mean for Efficiency and Innovation?

Identifying, sharing, and distributing knowledge is a capability that a few companies have fully developed. Organizations embracing KM processes are more likely to have a strong commitment to improving efficiency and innovation compared to peers not involved in knowledge-related practices. As a result, the likelihood of filing more patents increases and employees acquire deeper tacit knowledge. To illustrate this pattern, one might look at the annual ranking of the top 50 U.S patent assignees across sectors from IFI Claims Patent Services (IFIClaims)—a patent research company. For example, technology company IBM had a record 9,043 patent grants in 2017 representing a strong +12% increase compared to the same period in 2016. IBM patents in 2017 reflect innovations in data management and application development, among others. The following are IFIClaims’ top 20 most innovative companies for 2017 and 2016 based on the number of U.S patent grants received:

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Note: Year 2017 reflects data as of January 1, 2018 and year 2016 data as of January 1, 2017.

Organizations around the world are increasingly engaged in innovation and efficiency, both of which reflect KM systems. Overall, 2017 was another solid year for U.S patent grants received by organizations worldwide. The graph below shows that of the record 320,003 U.S utility grants approved in 2017, U.S corporations accounted for most of them at 46.29% followed by Japan with 15.81%.

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Despite the benefits, managing a KM program may raise salient challenges: (1) weak senior management leadership and support, (2) knowledge hoarding, (3) increased costs, and (4) dysfunctional corporate culture. Knowledge hoarders gather know-how and information for personal use, thus preventing knowledge sharing. In his article, John Edwards explains that organizations may also incur economic losses arising from their limited ability to process structured or unstructured data. Structured data involves information with a high degree of organization and is easily identifiable by search engine algorithms. Meanwhile, unstructured data consists of images, text, and other content not organized in a clear method. This requires material resources to produce meaningful business intelligence. For these reasons, Thao Hua states that true cases of KM adoption have been few and far between among organizations i.e. asset management firms.

Knowledge Management in Practice

Although the application of KM is challenging, companies should consider integrating KM systems more prominently in their business strategy.  The extent of dedicated resources will vary depending on a company’s scale and scope of business. For example, publicly-traded companies like German-based software company SAP SE (NYSE: SAP) and U.S.-based asset manager BlackRock Inc (NYSE: BLK) are actively involved in content and knowledge-driven  initiatives.

To illustrate, in July 2018, SAP announced that its SAP Preferred Success Plan clients will also have access to the SAP Learning Hub Solutions edition. Both services help clients maximize the value from their investments in cloud solutions. SAP gave unlimited cloud resources access to five IT administrators per client. Such resources include expert-led social learning, structured learning content, and live sessions, all of which will allow SAP to share knowledge with clients and collect it from them too. SAP executives expect these solutions to further develop clients’ skills, or tacit knowledge, to create future innovations. From a cost-benefit perspective, using KM can reduce costs. For example, SAP states that appropriate training of cloud software project teams, which means increasing tacit knowledge, could save clients about 10% in deployment time. These cost savings will positively contribute to clients’ efficiency and budget. As a side note, SAP has a Chief Knowledge Officer overseeing product and innovation initiatives.

The benefits of using KM are also visible in the asset management industry. KM can improve the economics of new investment product offerings, data analytics, and human capital time allocation. BlackRock boosted its new product development and value-adding services by endorsing KM systems and introducing a learning culture across the firm:

First, it created the BlackRock Investment Institute (BII) in 2011. BII has two functions: a knowledge center and a liaison between its investment/research activities and clients.

Second, BII is elevating knowledge communication through technology. The firm is creating a new Global Head of Content position reporting to the Chief Marketing Officer. Existing KM and technology positions include Chief Engineer Officer and Chief Information Officer. The new role will focus on content strategy, distribution, and analytics across technology platforms, which could shape how the firm’s KM systems will be used. For example, gaining first-hand knowledge of selected clients’ investment processes could allow the development of tailored content for each stage of the process. This specific content can then be distributed to clients on a timely basis.

Lastly, BlackRock is advancing its known appetite for innovation and hastening the use of artificial intelligence (AI) for multiple purposes. The firm’s “Tech 2020” plan involves endeavors to further integrate technology and knowledge. These efforts should contribute to higher profitability, growing asset under management, and better performing business processes—both internally and externally:

Internally, employees and the company benefit from using AI for algorithmic trading, active equities strategies, data science, and research. A few years ago, BlackRock embarked on AI-related efforts. Yet, it faced some challenges during implementation, namely employee turnover, the need for new AI skills/training, and limited AI back-office operations/infrastructure. The firm mitigated these challenges by (1) setting up programs to accelerate employee learning, (2) enhancing knowledge-sharing platforms, and (3) acquiring or partnering with technology startups (i.e. optimization, natural language processing), according to BlackRock’s Jody Kochansky. Having now developed a track record in AI, in February 2018, BlackRock created the BlackRock Lab for Artificial Intelligence and an internal Data Science Core team. These actions will respond to evolving client needs identified by the firm.

Externally, clients benefit from BlackRock’s seven AI-based Sector ETFs launched in March 2018. Leveraging BlackRock’s in-house expertise, the firm may create other AI-driven ETFs to include additional countries—which might be a reality in the not-too-distant future. This could translate into potential economic and brand benefits for the firm. By using AI knowledge, BlackRock is transforming its business model while broadening its iShares ETF product line.

To conclude, KM involves a formal process to identify, manage and deploy knowledge within the firm. It also involves the ability to deploy knowledge externally through client contact or product innovation. Through technology, knowledge is shared and distributed to the right people at the right time—which are key to organizational efficiency and productivity. Incorporating a KM perspective into organizational strategy helps a company plan employee training, product development, and IT investments. This can be achieved by using KM tools such as customer relationship systems and learning management systems. Ultimately, putting KM into practice has challenges; however, integrating it is beneficial for corporate competitiveness and long-term success.

Works Cited

Image Source – Cover: https://www.shutterstock.com/image-vector/gears-knowledge-management-mechanism-385714435?src=IqcCNnkWH-YYh80a4eWO2w-1-46

Image Source – Explicit vs Tacit Knowledge: http://www.knowledge-management-tools.net/different-types-of-knowledge.html

Image Source – Data to Wisdom: http://www.knowledgemappers.com/news.php

Image Source – IFIClaims Ranking: https://www.ificlaims.com/rankings/rankings-top-50-2017.htm

Image Source – IFIClaims 2017 U.S Utility Grants by Country: https://www.ificlaims.com/rankings-trends-2017.htm

BlackRock Investment Institute BII. Retrieved November 7, 2018 from https://www.blackrock.com/corporate/insights/blackrock-investment-institute

Dalkir, K. (2005). Knowledge Management in Theory and Practice. Burlington, MA: Elsevier Butterworth–Heinemann.

Edwards, J. (2018, August 16). Getting Smart About Knowledge Management. Retrieved November 10, 2018 from https://www.informationweek.com/software/getting-smart-about-knowledge-management/d/d-id/1332532

Hua, T. (2013, September 30). Knowledge management underutilized by money managers. Retrieved November 10, 2018 from http://www.pionline.com/article/20130930/PRINT/309309975/knowledge-management-underutilized-by-money-managers

IFI Claims Patent Services. (n.d.). 2017 Top 50 US Patent Assignees. Retrieved November 18, 2018 from https://www.ificlaims.com/rankings-top-50-2017.htm

Kochansky, J. (2018, March 8). The promise of artificial intelligence and what it means to BlackRock. Retrieved November 10, 2018  from https://www.blackrockblog.com/2018/03/08/artificial-intelligence-blackrock/

Lurie, I. (2012, March 22). Information is free. Knowledge is not. Retrieved November 10, 2018  from https://www.portent.com/blog/random/information-is-free-knowledge-is-not.htm

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