What KM can learn from start-ups - 5, build a good product

Last week I started a set of blog posts likening KM implementation to a business start-up. Here is number 5 in the series. 

Lean Start-up methodology, by Rebeca Zuniga on Flickr

This blog series uses this analogy of a start-up to inform KM implementation. It reviews 5 common reasons for start-up failure and suggests ways in which KM programs can avoid these failure modes. These common reasons are taken from  a great article by David Skok , and are as follows:

1. Little or no market for the product; 
2. The business model fails; 
3. Poor start-up management team; 
4. Running out of cash; 
5. Product problems.

Ensuring the Product meets the market need

The final reason that start-ups fail is because they develop a product that doesn’t meet the market need. In our case, the KM product is the management framework we introduce to the business, comprised of roles and accountabilities, processes, technology tools, and governance.

This failure mode often happens when the product is developed in isolation from the users, and turns out to be not what the market wants. An approach commonly used to avoid this pitfall is the Lean Start-up or Agile approach, where products are developed through an iterative series of prototypes. “Minimum viable products” are released to early adopters in cycles of Deploy, Measure, Learn, and the learning from each cycle is used to improve the product for the next cycle.

A minimum viable product is the simplest version of a product that will still add value to the customer, and the design team then use customer feedback to elaborate the product further. The piloting phase of KM implementation can use a similar approach.

KM Piloting has 4 objectives:

1. To gain learning about the application of the KM framework, which can be used to improve the framework and so develop it into a product that fits the market need; 
2. To test the market; 
3. To demonstrate value through KM in order to justify further investment, and 
4. To create success stories and user testimonials for marketing purposes. 

 In order to satisfy the first of these objectives, it makes sense to pilot, as early as possible, a minimum viable KM framework. This will not be a single KM tool, as one tool is not a framework. Instead it will be a complete but bare-bones management framework. And in order to satisfy objective 3, the bare-bones Framework should be applied to solve a real business problem. 

 For example, one organisation set up a simple KM framework to address problems in Production Engineering. A volunteer community coordinator set up monthly discussions using dial-in conference calls among a dozen enthusiasts around the globe, to discuss an identified agenda of critical knowledge issues. This minimum system added real value and solved several problems, and over time was extended to become a community of practice of several hundred people with a dedicated portal, software, meetings, roles and governance.

 Starting small and growing allowed the KM Framework to be tested at every step, and ensured that the final version of the Framework was exactly what the users needed in order to add value. The product grew to match the market need.

Use an Agile piloting approach to ensure your KM Product is tailored to the market

What KM can learn from start-ups - 4, ensure the flow of funds.

Last week I started a set of blog posts likening KM implementation to a business start-up. Here is number 4 in the series. 

Image from wikimedia commons

This blog series uses this analogy of a start-up to inform KM implementation. It reviews 5 common reasons for start-up failure and suggests ways in which KM programs can avoid these failure modes. These common reasons are taken from  a great article by David Skok , and are as follows:

1. Little or no market for the product; 
2. The business model fails; 
3. Poor start-up management team; 
4. Running out of cash; 
5. Product problems.

Managing the flow of funds so you don't run out of cash

A fourth major reason that start-ups fail is because they ran out of cash before they reach the next refinancing milestone or achieve positive cash flow.

The same is true for KM. A KM implementation budget may be needed for over a decade, and the annual budget will usually increase during that time. It will be very difficult to secure the totality of such a budget in advance. Instead the KM team can learn from business start-ups and seek funding only as far as the next investment milestone.

 There are 5 main milestones or decision points in a KM implementation project which can be linked to the assignment of additional funds. At each of these milestones the budget is likely to increase.

1. The initial funding milestone is a decision to fund a temporary task force to determine whether KM is of sufficient potential interest that a KM team should be formed.

 2. The second milestone is a decision to fund a KM team to conduct the Assessment phase. The team will investigate the potential value to be gained through KM, the market for KM within the organisation, the needs of the stakeholders, the size of the potential prize, the current state of KM in the organisation, and how much investment is required. They will output a KM business case, strategy and implementation plan, and will make the case that the potential value in KM merits further funding.

3. If the KM team has made the case for investment in KM implementation, they will request a budget to fund the piloting stage. This decision allows the team to start testing and piloting initial KM approaches and prototype versions of the Framework within the organisation, focusing on solving business problems. Part of the purpose of the piloting stage is to gather data to show that KM delivers more value than it costs, and to justify the next decision.

4. The fourth decision comes at the end of the piloting stage, in order to fund the roll-out stage. If the pilots were successful, the value of KM to the business and to the employees has been proven, and the integrated KM framework has been tested in the business and shown to be robust. Now the organisation needs to fund roll-out of the Framework to the whole organisation.

 5. Once KM is embedded, the fifth milestone involves standing down the implementation team and handing KM over to a management team. At this stage funding will be operational funding rather than project funding. This phased approach, where investment for each phase is justified by the work of the previous phase, allows for an escalating set of evidence-based financing decisions and should ensure the KM budget does not run dry.

An alternative approach is to fund the program on an annual basis. This is what Mars did, according to Linda Davies, quoted in The Knowledge Manager's Handbook.

"From the beginning, KM was run as a separate division with its own business plan, detailing how and why KM was to be implemented. The business plan followed standard business planning practice, with a broad three year time horizon and a detailed one year plan submitted annually as part of the regular business planning cycle. This detailed the overall objectives for the following year, the timescale for the planned activities plus the costs and resource requirements.... 

The power of focusing on two or three challenges in any one year became apparent, resulting in rapid progress and big wins and proving the concept of the value that KM can bring to the business. This led to a regular increase in KM budget and resource which enabled subsequent initiatives"

Think through how you will ensure you have the funds flow you need for KM implementation, and use successes to prove the concept and access the next stage of funding.

What KM can learn from business start-ups 3 - appoint the right team

Last week I started a set of blog posts likening KM implementation to a business start-up. Here is number 3 in the series. 

Picture from Needpix, author geralt (pixabay.com)

This blog series uses this analogy of a start-up to inform KM implementation. It reviews 5 common reasons for start-up failure and suggests ways in which KM programs can avoid these failure modes. These common reasons are taken from  a great article by David Skok , and are as follows:

1. Little or no market for the product; 
2. The business model fails; 
3. Poor start-up management team; 
4. Running out of cash; 
5. Product problems.

Poor start-up management team

According to Skok's article,

"An incredibly common problem that causes startups to fail is a weak management team. A good management team will be smart enough to avoid Reasons 2, 4, and 5. Weak management teams make mistakes in multiple areas: They are often weak on strategy, building a product that no-one wants to buy as they failed to do enough work to validate the ideas before and during development. They are usually poor at execution, which leads to issues with the product not getting built correctly or on time, and the go-to market execution will be poorly implemented. They will build weak teams below them. There is the well proven saying: A players hire A players, and B players only get to hire C players (because B players don’t want to work for other B players)"

The choice of the KM Implementation leader, and the KM team, is crucial. We have also seen that a poor KM team is a common cause of KM implementation failure. The team leader should be:

• A Change Agent, with  a history of delivering organizational change
• Familiar with the risks involved in change programs (and business start-ups)
• A respected senior member of the organization
• Charismatic, engaging and influential
• A confident and effective communicator, with excellent leadership skills 
• Not afraid to take risks 
• Diplomatic
• Familiar with the technology and the human/cultural issues involved in KM
• Very familiar with the organizational structure, vision and strategy
• Well networked within the company

If we look at the work of the KM team during KM implementation, we can see the following stages:

• An analysis or "market research" phase, some of the activities of which are described in the first post in this sequence. During this stage the KM team will create the KM strategy, survey the internal “market”, determine the stakeholders and their value propositions, create the business case for KM, and plan the next stages of the implementation program. The team in this phase needs to be strong in strategic thinking and understanding stakeholder needs. 
• A piloting phase, during which a simplified prototype KM Framework is progressively tested with the business, improved and elaborated, as we will discuss later this week. The team in this phase needs to be strong in the mechanics of KM (e.g. the facilitation of KM processes, KM technology and Information Management), as well as working with business customers and leaders, and communication and marketing. 
• A roll-out phase, during which the final KM Framework is deployed across the organisation through engagement, training and coaching. The team in this phase needs to be strong in influencing, selling and marketing. 
• A operation phase, during which the use of the KM Framework is supported monitored and measured across the organisation. The team needs to be strong in the mechanics of KM, and in analysis of the value delivered and the opportunities for further improvement of the Framework.

A strong leader such as described above can build a strong and balanced team, which needs the following skills mix:

• Facilitation skills. 
• Coaching and training skills. 
• Marketing/influencing/selling skills 
• Writing skills. 
• Technology skills. 
• Information management skills

There seems a tendency, which we have seen many times, to appoint teams made up entirely of information managers and librarians. The thought process seems to be

• "Knowledge is a little bit like Information" (wrong assumption number 1 - knowledge is not at all like information, although there is a small area of overlap)
• "If the KM team is managing knowledge, then they need information management skills" (wrong assumption number s 2 and 3 - the team is not managing knowledge, they are influencing the organisation to management knowledge, and  the primary skills they need are influencing skills, not IM skills, although you need some IM skills to cover the area of overlap).

Think like a start-up. Your KM Implementation leader should be a Jobs rather than a Wozniak, and the team should be selected as if they were trying to introduce a new product into a market (which is actually what they are doing).

What KM can learn from business start-ups 2 - an effective business model

Yesterday I started a set of blog posts likening KM implementation to a business start-up. Here is number 2 in the series. 

Picture by Tumisu (pixabay.com) on Needpix

In many ways, the initial implementation of Knowledge Management within an organisation is like the launch of a new product into a market by a start-up organisation, and there are many lessons KM can learn from start-ups; their failures and their successes.

(If you want to make a bad pun, you could call KM implementation a "Smart-up").

This blog series uses this analogy to inform KM implementation by reviewing 5 common reasons for start-up failure and suggesting ways in which KM programs can avoid these failure modes. These common reasons are taken from  a great article by David Skok , and are as follows:

1. Little or no market for the product; 
2. The business model fails; 
3. Poor start-up management team; 
4. Running out of cash; 
5. Product problems.

Failure of the business model

The business model for a start-up fails if the cost of acquiring new customers exceeds the value each customer brings. If this happens, the start-up will lose more and more money until the investors remove their support.

As David Skok says, "One of the most common causes of failure in the startup world is that entrepreneurs are too optimistic about how easy it will be to acquire customers. They assume that because they will build an interesting web site, product, or service, that customers will beat a path to their door. That may happen with the first few customers, but after that, it rapidly becomes an expensive task to attract and win customers, and in many cases the cost of acquiring the customer (CAC) is actually higher than the lifetime value of that customer (LTV)".


KM also has a business model. KM receives funding from senior managers, who are  the investors in the "KM start-up". Those investors want a return on their investment, in whatever way they define "return". The KM Implementation must deliver more value to the business than it costs (e.g. deliver a positive ROI), and those costs include the costs of the KM team, KM software, and the costs of implementation, roll-out and support ("acquiring the KM customers").  This positive return must be documented and justified in order that senior management do not remove their support and their money.

In addition, KM is a long term commitment; survey data shows that it takes over a decade before KM is fully integrated in the majority of companies. This is a long time to take KM value on faith, and the viability of the business model needs to demonstrated on a regular basis throughout that decade if funding is to be secured.

Also, during that time there may well be a change in senior management, and the new bosses may need convincing that KM has a positive business model for the organisation. You need to have your evidence ready that KM is a wise investment. Internal reorganisation, and a change in investor, is one of the most common reasons for KM failure, and you need to protect against this.

In order to demonstrate a positive return on investment, the KM implementation team needs to:

• Understand the metrics that will convince senior management that KM is delivering a return on investment. Know what they want to see from KM, and know how this will be demonstrated or measured 
• Conduct short term pilot projects throughout the implementation that deliver demonstrable value, as proofs of concept that KM has a positive business model. These pilot projects should solve business problems, and ideally should impact business metrics. Early in KM implementation the KM Framework will still be in process of development, so use a Minimum Viable Framework - one that does just enough to deliver real value. The pilot will also deliver practical lessons that allow you to elaborate the framework.
• Collect and regularly report all examples of value delivered through KM, in the form of success stories and/or metrics. These will not only allow you to demonstrate a positive business model to your sponsors, showing that KM delivers more value than it costs; it will also provide valuable marketing collateral for further KM roll-out. 

Bear in mind the business model for KM, and how you will demonstrate that it is viable. Without this demonstration, you are vulnerable to losing your funding. 

What KM can learn from business start-ups - ensuring there is a market

If we liken KM implementation to a business start-up, there are many lessons we can learn and apply.

Image by www.inkmedia.eu on Flickr

In many ways, the initial implementation of Knowledge Management within an organisation is like the launch of a new product into a market by a start-up organisation.

You are preparing something which, in theory, is designed for a customer base of users, and which will you hope they will find valuable enough to adopt. Your product is a Knowledge Management Framework, your customer base are the knowledge managers within an organisation, your start-up company is the in-house KM team, and your investors are the senior managers who provide your budget.

The launch of new products by start-ups is fraught with difficulty. 20% of start-ups do not survive their first year, while 50% have failed before the end of their 5th year. Failure rates for Knowledge Management are often quoted as being in a similar range. Obviously both undertakings are far from easy, and arguably there may be much that KM can learn from business start-up.

This short series of 5 blog posts uses this analogy to inform KM implementation by reviewing 5 common reasons for start-up failure and suggesting ways in which KM programs can avoid these failure modes. These common reasons are taken from  a great article by David Skok , and are as follows:

1. Little or no market for the product; 
2. The business model fails; 
3. Poor start-up management team; 
4. Running out of cash; 
5. Product problems.

This blog post explores the first of these 5, and the others will be covered over the course of the next week.

Failure mode 1 - Little or no market for the product

How do we ensure there is a market for the KM product we build?

 David Skok describes this failure mode as occurring when there is little or no market for the product the start-up has built. In other words, there is not a compelling enough value proposition to cause the buyer to actually commit to purchasing. This could be because the product does not fulfil a buyers need, or the market is not yet ready, or the customer base is too small. Whatever the reason, you have built a product for which there is no market.

We see this in KM implementation when we roll out our KM Framework and KM solution, and there is little uptake. We have built something nobody wants.

This failure mode can be addressed initially by proper analysis of market needs before KM implementation begins. It will also be further addressed by "Agile" product development, which I cover in a later post.

Any KM implementation program should begin with a thorough analysis of the internal market for KM, the value proposition for all stakeholders, a preliminary view of the “gap in the market” and a clear understanding of the KM USP within the organisation.

The ISO standard 30401:2018 suggests three foundational activities for KM, described below, which help with this market analysis.

 Understanding the organization and its context 

This involves an analysis of the external and internal issues that affect the organisations ability to achieve the intended outcome of its KM Framework; the market constraints if you will.

Understanding the needs and expectations of interested parties (stakeholders) 

This involves identifying the stakeholders for KM, and their requirements. In Siemens they recognised two main classes of stakeholder, “the business” and the user. We can add a third to this, to determine three primary internal stakeholders for Knowledge Management; as follows:

• Senior management; those who sponsor the KM program. In the analogy with a business start-up, these are the investors. They want to see a return on investment, in whichever way they define it. It may be a financial ROI, or it may be “fewer mistakes”, “less rework”, “better customer satisfaction” or some other metric. 
• The knowledge workers, who will benefit from use of the KM Framework. In the analogy with a business start-up, these are the end users, or consumers. They want KM do do something for them that is more valuable than the time of effort required to take part. Perhaps KM will make their life easier or less risky in some way. 
• The middle managers, whose cooperation you need in order to adopt KM within their teams. In the analogy with business start-up, these are the dealers or the retailers. They “buy” KM from you in order to “sell” it to their teams of knowledge workers. They will adopt KM in order to make their teams more efficient or more effective. 

The KM team should not only identify these stakeholders and their needs, they should develop a value proposition for each stakeholder group in order both to understand what KM needs to do to deliver value to the stakeholder, and also to be able to effectively market and sell KM.

To these activities we can add a third:

Identifying the USP for KM

You need to be able to say what KM does that is new and different; it's Unique Selling Point. It could be something like:

• KM eliminates the cost of lost knowledge (and it helps if you can value that cost)
• KM helps you find the knowledge you need to do your job
• KMis the driver for continuous improvement across the organisation.

This can be the basis for your KM vision, brand, strapline and marketing campaign.

If you can do your market research as described above, then you can be assured that there is a market for KM, and can start to design your product to satisfy that market. 

The link between Big Data and Knowledge - the classic Walmart story

This is a short analysis of the story of WalMart's preparation for hurricanes, in order to explore the link between Big Data and Knowledge.

Hurricane Irma food distribution, by City of St Pete on Flickr

One of the earliest and most famous "big data" stories is around Walmart and it's analysis of sales data related to hurricanes.  Let's look at this story through the lens of "Observation, Insight, Lesson" to see the link between Big Data and Knowledge.

According to the New York Times in 2004 -

A week ahead of (Hurricane Frances) landfall, Linda M. Dillman, Wal-Mart's chief information officer, pressed her staff to come up with forecasts based on what had happened when Hurricane Charley struck several weeks earlier. Backed by the trillions of bytes' worth of shopper history that is stored in Wal-Mart's computer network, she felt that the company could "start predicting what's going to happen, instead of waiting for it to happen," as she put it.

The experts mined the data and found that the stores would indeed need certain products - and not just the usual flashlights. "We didn't know in the past that strawberry Pop-Tarts increase in sales, like seven times their normal sales rate, ahead of a hurricane," Ms. Dillman said in a recent interview. " 

And the pre-hurricane top-selling item was beer."Thanks to those insights, trucks filled with toaster pastries and six-packs were soon speeding down Interstate 95 toward Wal-Marts in the path of Frances. Most of the products that were stocked for the storm sold quickly, the company said. Such knowledge, Wal-Mart has learned, is not only power. It is profit, too.

This story is a classic example of the power of Big Data, but let's look at it through a Knowledge lens.  The Military model of knowledge development is that it comes through a 3-step process of Observation, Insight, Lesson, and that the Lesson then leads to Action. The New York Times suggests that the big data algorithms delivered knowledge, but I suggest that what they delivered was Insight, and that the Knowledge is applied when you know what to do with those insights.

• The "trillions of bytes' worth of shopper history" is a collection of Observations
• The correlation of shopper behaviour with imminent hurricane landfall is an Insight
• The lesson, on which action will be based, comes from an analysis of the insights with a background understanding of Walmart's business and strategy. 

I would disagree with the New York Times. I think that what the data-mining experts found was Information in the form of a Correlation. The Knowledge would come in knowing what to do with that information (Knowledge, after all, being what enables correct action).

What would you do, dear reader, if you were a Walmart Executive who had been given this information on beer and pop tart sales? What action would you take?

• Should you (as the New York times suggests) stock your stores with extra supplies to increase profit?
• Should you (as this article suggests) put Pop-Tarts near the store entrances during hurricane season so that sales can "soar"?
• You could even consider raising the margin on these items, following the principles of supply/demand pricing?

All of these solutions will increase sales and improve profit, but would Walmart really want to use a hurricane solely as an opportunity to increase profit? That might not go down so well with the public.  As Peter Drucker said, "Information only becomes knowledge in the hands of someone who knows what to do with it" and luckily Walmart has the knowledge they need to use this information wisely.

What Walmart actually do 

Walmart have built their own "best practice" for disaster relief (here, from page 177)  In the US this includes

• Making sure their own stores are reopened as soon as possible 
• Providing merchandise for emergency responders, such as bottled water for first responders, office supplies for command posts, flashlights and batteries for search and rescue crews
• Donating pallets of dry food, soft drinks, flashlights, clothes, blankets and childrens board games
• Hosting massive barbecues in their parking lots, to feed citizens with no domestic power

 As a result WalMart is seen as a lifesaver, and it's disaster response procedure has been compared favourably with that of FEMA. They have won the hearts of the public, and of the administrators.

Walmart are winning on three counts. They have plenty of observations in the form of shopper data, they analyse this data to derive insights, and they have knowledge (based on experience and codified in best practice) that allows them to take the correct actions. 

It is that knowledge that allows them to know what to do with the insights they mine from Big Data

NASA's "5 most common KM mistakes"

In a 2015 video reprise from Edward Rogers, CKO of NASA Goddard, he explains what he sees as the 5 most common mistakes in implementing KM.

All of these stem from one reason, which is that KM people too often fail to learn from the experience of the past. Edward's 5 reasons for failure are these;

1. Attempting to implement a KM system in a hurry, by "buying a KM program". KM at NASA has been a 10 year proposition.
2. "Gaming" KM; trying to manipulate people though tricks and incentives
3. Applying a KM framework "off the shelf" rather than tailoring it to your own context
4. Selling KM with an unrealistic revenue target (but also see his video on quantifying the value of KM pilot projects)
5. Letting IT and the CIO handle KM, which ends up with a data and information system, not a KM system

Compare these with our list of the most common reasons KM programs fail