On a recent flight, I had an engaging conversation with the CEO of a large global company. After broadly discussing the business environment and how he is leading his organization through the changes taking place globally, I asked him about some of the current issues and challenges that he is currently focused on. Among the top 3 mentioned were:
– technology is the business now, not just the enabler;
– bridging the skill gap required for his vision of the company; and
– pushing the team to learn to ask the right questions with customers, partners and suppliers.
It was the last one that caught my attention as I was intrigued by the behavioral issue he had raised, “Are we asking the right questions to learn and listen more, build collaborative solutions or are we just putting out there about what we know”?

One of the most interesting points I captured from this conversation was about the effectiveness and business impact this key aspect has created in his company. At his organization, the teams which are able to ask the right questions to their ecosystem of customers, partners, suppliers, etc. have consistently outperformed the rest by 50+% across multiple quantifiable parameters. Why should asking the right set of questions be difficult? Why should everyone not be able do this naturally? Does this need training and coaching? Who asks the best and leading questions? They may often make it seem effortless, and yet they need much experience and knowledge on the subject, along with a broad set of business acumen in technology, domain, industry, people, process, and of course, a curious and open mind.

In the fast changing world, where every industry is massively disrupted by technology, where software is impacting every business, where digital, mobility, data science, cloud, cybersecurity, predictive analytics, etc. have become mainstream, and where partnership is the mainstay to deliver overarching solutions for an effective business outcome; any meaningful solution can only be achieved through intense collaboration. Collaboration comes through leading with thoughts and asking the right set of questions. Engaging in thought-provoking conversations and often asking counter-intuitive questions are key for a full view of the opportunity dimensions, and also helps us think through multiple scenarios of an issue as well as be a useful guide in crafting possible solutions. It is important to focus on enabling the thoughts rather than providing instant answers. It is important to learn to ask the right questions.

Considering the different phases in a clinical trial, there is a need for subjects to be enrolled according to the eligibility criteria defined in the study protocol. Holding the involvement of the right patients is a critical barrier for investigators and sponsors. During the conduct phase of clinical trials, sites usually spend most of their time working on patient recruitment, and yet, statistics show that despite this effort, reaching enrollment goals according to the timeline is frustratingly elusive in many studies.

The industry perspective reflects that it is the unabridged responsibility of the investigator to recruit and retain patients in clinical trials. The methodology adopted is very generic in nature and the same sets of patients from internal databases are referred for different trials. Trends suggest that most of the prescreened eligible subjects are lost before they are enrolled.

 

There is a need to leverage contemporary technology methods and databases like using Social Media for broadcasting of trials, using healthcare industry databases (HCUP, APCD, etc.) covering Electronic Medical Records, Hospital Discharge Summaries, Claims Data, Patient Registries, Sponsors Internal Databases, and more, to identify the right sites and the right patients. Patient recruitment efforts can be further amplified by mapping and matching patients’ profiles on Blue Button, shared by them to solution providers. The effective use of this information will direct them to precisely register in the right study.

 

Once enrolled, they need to be supported with the right information and care through the right channels for retention and adherence, as per the study protocol. Solution frameworks supporting the above requirements, depend on: 1) An Information layer to identify the right datasets; 2) An Intelligence layer to apply the inclusion/exclusion criteria; and 3) An Interaction layer to retain the enrolled patients.

 

For more details, please visit: http://www.hcltech.com/white-papers/life-sciences-and-healthcare/patient-recruitment-and-retention-strategy-clinical-trials

Sandeep Kishore, HCL Technologies, explores digitalisation and the role that a Chief Digital Officer can play in leading digitalisation projects.

Everywhere you look businesses are being reinvented and rejuvenated, utilising new technologies and tools in an effort to tap into the digital advantage. This process of digitalisation is as unstoppable as it is irreversible; businesses are investing heavily to stay afloat in the new digital age. As such, digitalisation has moved way beyond high-concept discussions at the board level, to the creation of detailed roadmaps and the implementation of new ways of working and service delivery. This change is bringing with it the ability for businesses to create unique customer-facing experiences, whilst driving greater back-office efficiencies.

Spending on digitalisation over the remainder of the decade is forecast to be enormous; contributing to over 80% of incremental IT expenditure. Indeed, IDC estimates that spending on cloud, social, mobile and analytics technology will reach around $940 by 2017. The compound annual growth rate is set to be three times greater in comparison with spend on traditional IT over the same period. This level of investment indicates that digital technologies will clearly have a major direct impact on businesses in the coming years.

Playing with the new kids on the block
Those that are most well suited to thrive in the digital era are perhaps unsurprisingly those businesses that were born digital and have none of the legacy infrastructure of more well-established companies. The savviest enterprises are looking to tap into this expertise, by working with native digital companies to better deliver unified, reliable and seamless customer experiences across a multi-platform environment. Furthermore, this approach can help to ensure better integration with suppliers and partners, such as payment providers; which delivers further operational efficiencies.

For example, in the media and entertainment industry, Netflix has emerged as an alternative to regular satellite and cable television services. For a fraction of the cost of the traditional alternatives, subscribers are able to watch any number of shows, at any time, on any screen. The success of this model speaks for itself; Netflix currently has 44 million subscribers globally. Low pricing is of course a key factor in this success, but just as importantly, Netflix is using analytics to deliver customised recommendations to each subscriber, suggesting additional content they may enjoy based on their viewing history. All this is made possible by cloud computing; which enables Netflix to deliver a previously impossible to achieve standard of service at such a low price without jeopardising its profits.

Enter the Chief Digital Officer
Of course, it is no mean feat for a traditional enterprise to achieve full digitalisation. There must be a significant commitment from within every level of the business to ensure that all teams are working towards a shared vision and goals. This means that the CEO and board-level executives must have direct visibility over the process to ensure the necessary levels of support and investment are made available.

In order to facilitate this process more effectively, many organisations have created the new role of Chief Digital Officer (CDO) to oversee digitalisation. The CDO is responsible for developing a clear roadmap for the enterprise in its transition to the digital era; clarifying the role of every business unit and securing the buy-in from each individual.

As you would expect, IT has a significant role to play on the road to digitalisation for any organisation. The IT team will be responsible for modernising applications and integrating all data across the enterprise. They must also enable access to the corporate network and resources through mobile devices, build cloud platforms and enhance the security architecture to enable all of this without introducing new vulnerabilities. It is also critical to ensure that users receive a consistent experience across all enterprise services; so digital architects and product strategists too have a significant role to play.

Of course, digitalisation is not a silver bullet to solve all of an enterprise’s problems. There is also no simple, one-size-fits-all approach to rolling out a digital strategy. Those beginning the journey to digitalisation must consider the individual circumstances of their business and identify the desired impacts and how they can best be achieved. This is a strategic decision and will need the involvement of the highest echelons of the company. It is also important to consider which functions can deliver the greatest value in the short-term, who will take the lead and whether it will be necessary to hire new talent to better oversee digital best practices.

It must also be decided whether to start by digitalising customer-facing services to improve their experience, or back-office systems to create greater efficiencies. Perhaps most importantly, businesses must consider how the culture of the organisation will need to adapt in order to deliver the best impact from its digital revolution.

Digitalisation is a continuous journey and will be a long-term commitment for those embarking upon it. However, it has huge potential to deliver significant business benefits and create strong competitive advantages in today’s challenging environment. Digitalisation is therefore not so much a choice as an imperative. Ultimately, it is a simple evolutionary principle; businesses will either adapt or die as the digital age continues to surge forwards.

By Sandeep Kishore, Corporate Vice President for Life Sciences, Healthcare, and Public Services, HCL Technologies

In an article titled, “How big data can revolutionize pharmaceutical R&D”, the McKinsey Global Institute estimates that applying big-data strategies for better informed decision making could generate up to $100 billion in value annually across the U.S. health-care system, by optimizing innovation, improving the efficiency of research and clinical trials, and building new tools for physicians, consumers, insurers and regulators to meet the promise of more individualized approaches.

A lot has been inked about the pharma and healthcare industry lagging behind the retail and financial services industries in the use of big data.  Our premise is that deep data, and not big data, is critical for healthcare.  Deep data is about combining the relevant data streams with domain knowledge and analysis, not merely pursuing data acquisition while hoping that “insights” emerge from correlation.  With the availability of new data streams like clinical trial performance, climate, adverse events reporting, personal medical devices, and more, the trick is to identify value in these data streams and merge the appropriate streams to gain new insights.  Determining value in the data streams and knowing which ones to merge requires domain expertise to visualize the use-cases.

When improving clinical trial efficiency, the key focus areas would be site selection, investigator selection, and patient recruiting.  Clinicaltrials.gov is an important data stream that provides a rich view of various trial sites, study parameters, investigators and site performance.  Mapping the competitive activity for trials can be built to identify white spaces for site selection.  Fig 1 below shows the trial locations for various solid tumor studies being conducted in California for a Sponsor and its competitors.  While the Sponsor seems to be active in Southern California, the competition seems to have a higher density of locations in Northern California.  If we were to drill down further and examine the number of studies per location being conducted for solid tumor (Fig 2), it presents a totally different picture for the Sponsor.  Competition is conducting more studies at the same or similar locations as the Sponsor, which could lead to challenges in patient retention.

Source: Clinicaltrials.gov, HCUP California 2011

Taking the next data stream – Hospital Discharge, can help identify patients with tumors at various hospitals (Fig 3).  When this information is overlaid on the trial sites, we can evaluate potential sites with lower competitive density.

Investigator performance can now be evaluated based on study parameters and trials across competitors.  When data streams across Clinicaltrial.gov and social media are combined we can get a fair measure of investigator experience (Fig 4) and any compliance or regulatory issues (Fig 5)

Fig 4: Investigator Experience

Fig 5: Compliance/Regulatory Issues

Domain knowledge is critical in creating the problem statement and evaluating data streams for incremental gain.  Deep data allows for an optimal way to structure problems, analyze data and evaluate results, as opposed to the big data approach of hoarding data and performing analytics to get insights.  As seen in the above example, while Clinicaltrial.gov is a thin data stream, its content allows for rich evaluation of competitive and investigator landscapes for trials.  Layering additional data streams like Hospital Discharge, the FDA site and other social sites allows us to build a nuanced view of potential sites/investigators for trials.  Similarly, deep data techniques could be utilized for better targeting of physicians, hospital key account management and patient therapy adherence.

Dynamic changes in legislation, patent expiry of block buster drugs, and increasing healthcare costs call for significant changes in the global pharmaceutical industry. These changes are driving pharma companies to explore pharmerging markets for personalized medicines, biopharmaceuticals and biosimilars, which are opening up opportunities for further growth. The pharmerging markets offer tremendous opportunities for pharmaceutical manufacturers facing mounting pressures in developed markets.

IMS defines pharmerging countries as those having more than $1 billion in spending growth from 2012 to 2016 and a per capita gross domestic product of less than $25,000. A few of the 17 pharmerging countries include China, Brazil, Russia, India, Latin America and others.

Global pharmaceutical sales are expected to grow about 3% annually from $955 billion in 2011 to nearly $1.2 trillion in 2016, with 17 pharmerging countries. These countries are estimated to represent 30% of the total sales in 2016, up from 20% of the total in 2011. The BRIC nations will account for $248 billion in pharmaceutical sales by 2016. It is anticipated that as economies grow and mature, they begin to spend more on health related issues.

Global pharma majors have been witnessing sluggish growth in developed markets and as part of their strategic vision they have made significant organic and inorganic investments into emerging markets in recent years.

In the recent decade there have been focused investments on China, Brazil, Russia and India, which has started yielding results. Some of the world’s leading pharmaceutical companies have already started realizing more than 25% of their growth from pharmerging markets.  All of the top 15 global pharmaceutical companies are accelerating efforts to strengthen their presence within them – either through R&D investments, licensing deals, co-marketing, and mergers and acquisitions.

One clear, outcome is that Pharma companies are very keen to make inroads into pharmerging markets. They also understand that a well-planned strategy with a good understanding of new regulatory norms is absolutely essential for long term success.

With dynamic changes in the regulatory norms being set by individual nations, data management and regulatory submission is becoming increasingly complex and would be a major challenge to pharmaceutical companies going forward. To overcome these challenges and avoid rejection from regulatory agencies, Pharma companies are today exploring options for a unified data management and submission platform /tool especially for managing data for pharmerging markets.

References:

http://www.dddmag.com/articles/2012/10/pharmerging-markets-drive-future-sales

http://www.imshealth.com/imshealth/Global/Content/Pharmerging/Document/Launch%20Evolution%20Across%20Pharmerging%20Markets.pdf

B2B marketing has been viewed as the process of marketing one’s offerings to corporations in contrast to B2C marketing which targets and markets to end consumers directly. Consequently, B2B marketing is thought to be bland and lacking in glamour compared to B2C marketing. While these notions have generally held true for a long time, B2B marketing as a practice has come a long way in the past ten years. Like so many other areas, B2B marketing has been significantly affected by the rise and proliferation of the internet. Several B2B industries have progressed from being oligopolistic to a state of healthy competition. B2B companies have had to adjust to this evolution, with the successful ones embracing the changing times, and sometimes, capitalizing on them.

A number of B2B companies such as Google and Alibaba have become household names. Intel is one of the most reputed and widely known brands. However, the myths associated with B2B marketing have continued, which I will humbly try and bust one by one.

Myth 1 – B2B marketing is not cool

Elon Musk’s SpaceX corp is a B2B company, which is founded on a vision to colonize Mars. This vision, coupled with a smart marketing strategy to get mindshare by leveraging the right forums, has made SpaceX one of the most admired brands in the world, and one of the coolest ones, too.

As compared to B2C marketing, B2B marketing deals with products and offerings that are often complex, which limit the number of buyers and decision makers. However, constraints are a seedbed for innovation. Intel entered into a deal with the football club FC Barcelona to have their logo inside the jerseys of the players – Intel Inside!

Similarly, when we realized that information dissemination could prove to be one of the challenges for two of the biggest verticals at HCL, we decided to take the whole content ecosystem to a mobile platform by launching state-of-the-art mobile apps which can be used by the customer as well. This is a first for the industry, which we expect will become the norm in years to come.

Myth 2 – B2B marketing is not active

The reasons why B2C marketing seems a lot more active than B2B are two-fold. Firstly, B2C marketing is targeting a large mass of customers at a go, and secondly, you are one of those customers.

B2B marketing is concerned with reaching the right audiences, and for those audiences, we are as active as we can be. We understand that 60% of the buying process is complete even before the customer meets a sales representative, and we strive to build a brand that helps us during the customer’s due-diligence process. At HCL, we work on a host of activities such as positioning, thought leadership, account-based marketing, digital and social, PR, and analyst relations. Speaking of positioning, we also invest a lot of effort in accurately segmenting our customers and striking the right positioning for us in the market. HCL’s Life Sciences and Healthcare vertical recently transitioned from a benefits-driven positioning to an emotional one.

Myth 3 – B2B marketers cannot do everything a B2C marketer can

A marketer is guided by the nature of the business and the people he/she is trying to reach. On these counts, B2C marketers do have a bigger playing field. At the same time, over the years, some of the biggest brands have been built in the B2B segment. IBM has proven to be one of the few technology brands that have stayed relevant over the years. ‘Smarter Planet’ is one of the most resonating positioning statements of today’s times. Caterpillar’s equipment playing a game of Jenga was one of the most viral videos of the year, and it fit like a glove in their value for precision. GE is a brand that has become the benchmark on newer social media platforms like Pinterest and Instagram. There are also a few things that B2B can do better. Marketing to a limited yet decision-making set gets HCL visibility right at the top level. For example, we got a chance to engage the CEO of one of the world’s leading pharmaceutical companies, which for us is the holy-grail of marketing.

Myth 4 – B2B marketing is about corporations and not people

It is a cliché but also true – corporations do not do business with corporations, people do business with people. A B2B marketer, just like his B2C counterpart, needs to understand the people who he is addressing. He needs to know their drivers, motivators, tastes, preferences, and the entire demographic and psychographic profile before planning a custom outreach plan.

At HCL, programs like CARS (Customer As A Rockstar) take this factor into account. We also ensure and keep in touch with the various influencer communities. #CoolestInterviewEver was a groundbreaking innovation on Twitter, where the entire recruitment process was conducted on Twitter; how’s that for transparency? Our Relationship Beyond the Contract (RBtC) Coffee Table Book is a unique asset which is aimed at the leaders of various organizations to directly engage them.

There are different ways to market a company. All companies do not need to spend money on Superbowl advertisement slots or YouTube campaigns for people to know about them. Elon Musk’s SpaceX is a fine example of this, with the mission and vision of the company ensuring that people talk about it. At the end of the day, a marketer – B2B or B2C – can only succeed if he understands the product and the customer thoroughly and plans timely interventions to capture the mindshare, and eventually the market-share.

The FDA’s regulatory requirements mandate the conduct of pre-clinical studies and clinical trials to establish product safety and efficacy of drugs, before they are launched in the market. Data from clinical trials represents the most pragmatic method of detecting possible new Adverse Drug Events (ADEs). They can be conveniently assessed by officers at the FDA and may be used to mark the drugs’ safety positioning / profile. These ADEs are listed, and the information about them is readily available on FDA’s website.

Once the drug is marketed, a healthcare practitioner, who suspects the prevalence of Adverse Drug Reactions (ADRs) or possible ADEs to a medicament, is obliged to share that data with the broader medical fraternity e.g., by submitting an article, report, data or letter to a medical journal or notifying the manufacturer of the suspect drug. In the case of a Serious Adverse Event (SAE), the same should be conveyed to the FDA as per the procedures. These spontaneous reports are a source of valuable evidence about drugs and medical   devices; predominantly about their rare, infrequent or delayed effects, and their safety in vulnerable subject populations. While pre-marketing and post-marketing trials deliver information about almost all safety issues with respect to population health, the only inherent drawback with the process is its diminished capacity to identify rare or unexpected effects of the investigational product.

Individual ADR reports to the FDA (by the medical practitioners or from the concern person), can make a substantial variance in the safety profile of a drug after it has been approved for use by a varied population group. However, experts have warned that even with the conduct of clinical studies with large sample sizes in a diverse population, there is a possibility that some of the safety issues may remain unidentified. One of the possible reasons for this is the extremely low occurrence of infrequent ADEs/ ADRs of prime public health concerns. Once the medicament is approved for marketing and is utilized by millions of individuals across geographies, the rare manifestation of these issues can transform into a substantial number of cases.

With worldwide digitalization, pharmaceutical industry is looking upon another channel to collect the information about possible ADEs of approved products, i.e. from the social media websites. This is now the need of the hour, as it is inevitable to avoid  the said data. Social media tools, which were not present till a few years ago, have become part of an individual’s life. Trends suggest that most adults in the US (>90%) have searched online for health information; this percentage has increased to more than 75% as compared to the previous year.

Thus, there is an immense possibility, yet to be explored in a ‘big way’ by the industry, to utilize the data on these social media sites for information on possible ADEs. This will help in further investigating and reinforcing the safety profile of the medicament. It is expected that if the data about possible ADEs exists in social media, then it shall be helpful for proactively mining, maintaining, building, and protecting information, which may be further leveraged to report to the FDA.

HCL’s in-house pilot analysis of data on social media – has been a testimony to the fact that this data can help to highlight and point-out the safety issues.  Also, it cannot be avoided or left unheard!

HCL has the required solution for effectively exploring this information. The solution is expected to have the positive impact in driving industry trends by extracting information about the possible ADRs/ ADEs from social media with precise accuracy.

A prospective industry view suggests that the role of CDM personnel is in a state of flux. This role is not only about accomplishing routine activities like designing case report forms (paper CRF/eCRF), annotating CRFs, designing databases, entering, validating and coding data, locking databases, and creating CDISC/analysis datasets, but also about stepping forward to meet all the expectations of the pharma fraternity. Here’s a quick list of some of these expectations:
■Augment the process of subject recruitment and retention in clinical trials
■Establish a vision for subject care, by maintaining subject profile and population health outcomes based on classifications such as – geography, gender, race, and more
■Extrapolate trial information for future use, with respect to medicine safety and efficacy, subject profile/disease information/drug price
■Evolve as a main subsidiary for risk based monitoring, centralized monitoring, and study site support
■Coalesce clinical trial data with Big Data, to help forecast trial success or to establish brand positioning, etc.
■Optimize the cost of clinical research with predictive analysis techniques
■Effectively manage links, alliances, associations and CRO data, based on historic performance and user friendly classifications, in order to help retrieve information by other teams of clinical research
■Enhance study digitalization for an overall boost in the processes

In most of the organizations, CDM managers have already established the procedural activities. They are, however, still struggling to find the right, most adaptable solution, which is made up of the right IT infrastructure that can support regulatory mandates.

The available software packages cannot sustain all activities at one time and are not adaptable enough to address constantly evolving regulatory requirements. Hence, these are not the preferred choice. But if chosen, the cost of licensing, validating, implementing and supporting them are high. When implemented, it takes considerable time to complete the training, and production time also increases because of complicated programming.

Stakeholders believe that primarily two work models can be adopted, to achieve desirable results:
■Work model 1: Develop a new, customized, low-cost software with all the capabilities built into it
■Work model 2: Integrate all individual (existing in-house) software into one common functional platform

The good news is that HCL can deliver tailored and regulatory-compliant support for both models. HCL can handle every contingency, help enhance data quality and enable timely regulatory submissions, cost-effectively. HCL helps organizations achieve their study/project/program objectives through the use of adaptable technology and the seamless integration of all their processes. And by taking on some of the tasks of the data managers, we free them up to focus on more crucial and strategic missions.

It is often very difficult to comprehend what knowledge means to an individual, professional, or an enterprise. The relevancy and authenticity of information is defined by the practical usage of the content in contextual paradigms. Other variable consideration such as content security adds to the information paradox which drives the complexity of defining Knowledge.

Enterprise knowledge management could be articulated as a combination of following statements:

• An authentic vault that houses knowledge of defined regimes / disciplines
• Secured information available to people with right access / roles
• Granular information driven by an organization taxonomy
• Knowledge driven by well-defined Information governance
• Information tagged and informed
• front end interface driven by find-ability / proximity and profiling

This blog attempts to define some key elements to consider before defining an enterprise KM. The blog also defines an adoption and KM portal evolution concept which is critical for the success of any Enterprise wide KM initiative.

Key Tenets for Defining a Knowledge Portal

For defining a knowledge portal it is important to categorize areas which will form the important pillars of the enterprise knowledge. Following are the key categories which will help initiate the process of creating an enterprise portal

• Know your Content – Information Architecture
• Define your Content – Content Governance
• Classify your Content – Taxonomy
• Qualify your Content – Content Tagging
• Improvise your Content – Content Back-feeding (Analytics)
• Value your Content – Content Rating & Community
• Advertise your Content – Profiling and Content Pushing
• Integrate your content – Content Multi-Sourcing

Know your Content – Information Architecture

Information Architecture (Referred as IA) is the most important pillar of defining a KM portal. IA provides a strong foundation of qualifying, categorizing, and segmenting content. A well-defined IA not only helps in increasing content find-ability but also promotes content proximity.

Information Architecture definition requires a well-balanced orchestrated blue printing exercise which attempts to define the following:

• Content Categories: All Content in a KM portal should be assigned to one or many categories. Categories helps in qualifying content and target find-ability
• Content Meta Data Model: Meta data based on content-type makes content rich qualified, and rationalized
• Content Relevance: Content should be constantly tracked and tagged. Segment content in popular, useful or ignore groups
• Content Security: content permission – create / update/ delete/ read/ Browse / Relate are critical to protect data integrity

Recommended approach for defining IA is as below:

• Identify a core group which works across streams
• Content Creators – Identify broad categories of content that needs to be part of the KM portal. Identify owners for each categories and have detailed workshop to hash out a detail IA architecture
• Content Readers – Identify profiles of all KM Portal users – have representation from all groups and track what they want from the portal.
• Explore the unknown – with the key stakeholders exploring what a standard KM portal should have from customer experiences
• The information collected from different groups should be collated and structured by the core group
• The IA would finally be run through all groups to iron out any changes required

Define your Content – Content Governance

Content Governance is next important tenet that needs attention for creating an informed KM Portal. Unlike other standard portal KM portal real work starts post the launch – it is imperative to keep information up-to-date, informed and visible for repeating visitors, inculcating stickiness, and growing community.

Content Governance has broadly the following elements to be defined –

• Clear definition of contributors: Active contributors, passive contributors (followers – adding additional content to existing content), specialized (Skill based)
• Region specific contributors: Qualifying only specific user to contribute certain content – all user can contribute trailing content
• Content Approval: Certain content needs to be approved before publishing to KM Portal
• Content Lifecycle: Multiple content lifecycle may exist based on the content types. Content lifecycle help define the state of the document throughout its lifetime. Some of the questions that content lifecycle can answer in content governance are – When to update content, when to expire content, when to approve and when to publish
• Content Integration: Federating content from external sources

Best practices for defining Content Governance is as follow:

• The IA output is the starting point for defining content governance For Content contributors go by categories – define roles instead of users.
• Bucket common categories and define sharable content lifecycles. The stages in the content lifecycle should have actionable items
• For every category – segment content that will be federated from external sources

Classify your Content – Taxonomy

Content Taxonomy is the most complex and critical element of a KM portal. Defining Taxonomy involves a detailed analysis of the content, categories, and content segments Taxonomy layering is typically done based on some defined parameters as mentioned below

• The User Community – Content should be taxonomically qualified for the user communities it represents
• Content Dictionary – Content Meta data related to a content dictionary – increase find-ability

Qualify your Content – Content Tagging

Once the metadata model is defined the content tagging can be done at either using System attributed or by using custom attributes as per a defined data model. The Content Tagging goes beyond the structured approach of getting content tags through a data model. Content Tagging helps to capture user generated information as tags which helps community to increase content segregation and relevance.

User Generated (UG) tags is a process which works post KM portal launch – The ability to capturing UG tags, comprehending the same for enhancing the experience is what we need to consider in the planning exercise.

Improvise your Content – Content Back-feeding (Analytics)

It is critical to know what content has been read the most, which category is most popular, how long user stays on a page, how communities are growing and how search is performing.

Strategy for content analysis or content behavioral analysis is important to calibrate the portal for broader acceptance

The best practices for defining content analytics are listed below:

• Qualify content categories and communities to be tracked
• Identify parameters to be tracked
• Create mechanism for back-feeding to improve KM portal usage improvements

Value your Content – Content Rating and Community Creation

For a successful KM implementation it is imperative to allow users to elevate the best information piece for everyone’s benefit. In a content cluster often it is paradoxical for consumers to accept the best content – upon finding its practical use it is important to mark such content for other similar users’ benefit.

Content Rating allows users to mark content contributors or the content itself for its applicability and usage. It also allows filtering such content first upon request to create a self-defined user community and qualify trustworthy contributors.

The KM portal should have provision for content rating, identifying star contributors and promoting best practices in communities of practice.

Advertise your Content – Profiling and Content Pushing

Often KM Portal pages or community contents are predefined based on a defined set of criteria. Though this approach traditionally works the best for vertical or horizontal portal, often this has become the main reason for a situation called “Content Stalemate” for KM Portal

In the new world content on a page or in a community should be governed by knowing who is visiting the portal and targeting content based on the contextual need. This kind of target content pushing is only possible when users are profiled, the needs are ascertained, and behaviors are comprehended.

The best of the KM portal has failed because of lacking capability to advertise its content in Just in Time mode. The KM portal should be equipped with the best in class profiling and content pushing strategy where information changes based on people point of interest and direction of usage

The best practices to avoid content Stalemate is by doing the following

• Identify a best of the breed Search tool
• Create Search lets and zero landing pages
• Inculcate profiling and content targeting features
• Blocking and boosting content
• Co-relation with taxonomy, folksonomy and content dictionary

Integrate your content – Content Multi-Sourcing

It is often not possible to have single source of truth – while a KM portal can put in practices of content identification, targeting, assimilation and distribution yet it should not target to become the only source of information.

Integration other content sources, within organization or from external sources , is equally important for a successful KM Portal.

There a numerous best practices which drives such governance –

• Implement Service based architecture – ability to consume content from multiple sources
• Drive the content philosophy from KM portal but allow all content to have a place
• Federation of Content – often it is not possible to index all content – specifically when the content is not in one’s control

KM Portal Definition Conclusion

The eight tenets towards KM Portal definition attempts in defining a strategy to create information centric content governance. These tenets do not define portal layout, technology recommendations, architectural best practices and physical installation. Neither does it define portal roles, roadmap and implementation strategies.

However, I strongly believe mastering these eight tenets is the first step towards a successful implementation and rest could be defined either in parallel or as post step to this phase