Untangling your organization’s decision making

It’s the best and worst of times for decision makers. Swelling stockpiles of data, advanced analytics, and intelligent algorithms are providing organizations with powerful new inputs and methods for making all manner of decisions. Corporate leaders also are much more aware today than they were 20 years ago of the cognitive biases—anchoring, loss aversion, confirmation bias, and many more—that undermine decision making without our knowing it. Some have already created formal processes—checklists, devil’s advocates, competing analytic teams, and the like—to shake up the debate and create healthier decision-making dynamics.

Now for the bad news. In many large global companies, growing organizational complexity, anchored in strong product, functional, and regional axes, has clouded accountabilities. That means leaders are less able to delegate decisions cleanly, and the number of decision makers has risen. The reduced cost of communications brought on by the digital age has compounded matters by bringing more people into the flow via email, Slack, and internal knowledge-sharing platforms, without clarifying decision-making authority. The result is too many meetings and email threads with too little high-quality dialogue as executives ricochet between boredom and disengagement, paralysis, and anxiety (Exhibit 1). All this is a recipe for poor decisions: 72 percent of senior-executive respondents to a McKinsey survey said they thought bad strategic decisions either were about as frequent as good ones or were the prevailing norm in their organization.

Growing organizational complexity and proliferating digital communications are a recipe for poor decisions.

The ultimate solution for many organizations looking to untangle their decision making is to become flatter and more agile, with decision authority and accountability going hand in hand. High-flying technology companies such as Google and Spotify are frequently the poster children for this approach, but it has also been adapted by more traditional ones such as ING (for more, see our recent McKinsey Quarterly interview “ING’s agile transformation”). As we’ve described elsewhere, agile organization models get decision making into the right hands, are faster in reacting to (or anticipating) shifts in the business environment, and often become magnets for top talent, who prefer working at companies with fewer layers of management and greater empowerment.

As we’ve worked with organizations seeking to become more agile, we’ve found that it’s possible to accelerate the improvement of decision making through the simple steps of categorizing the type of decision that’s being made and tailoring your approach accordingly. In our work, we’ve observed four types of decisions (Exhibit 2):

The ABCDs of categorizing decisions.
  • Big-bet decisions. These infrequent and high-risk decisions have the potential to shape the future of the company.
  • Cross-cutting decisions. In these frequent and high-risk decisions, a series of small, interconnected decisions are made by different groups as part of a collaborative, end-to-end decision process.
  • Delegated decisions. These frequent and low-risk decisions are effectively handled by an individual or working team, with limited input from others.
  • Ad hoc decisions. The organization’s infrequent, low-stakes decisions are deliberately ignored in this article, in order to sharpen our focus on the other three areas, where organizational ambiguity is most likely to undermine decision-making effectiveness.

These decision categories often get overlooked, in our experience, because organizational complexity, murky accountabilities, and information overload have conspired to create messy decision-making processes in many companies. In this article, we’ll describe how to vary your decision-making methods according to the circumstances. We’ll also offer some tools that individuals can use to pinpoint problems in the moment and to take corrective action that should improve both the decision in question and, over time, the organization’s decision-making norms.

Before we begin, we should emphasize that even though the examples we describe focus on enterprise-level decisions, the application of this framework will depend on the reader’s perspective and location in the organization. For example, what might be a delegated decision for the enterprise as a whole could be a big-bet decision for an individual business unit. Regardless, any fundamental change in decision-making culture needs to involve the senior leaders in the organization or business unit. The top team will decide what decisions are big bets, where to appoint process leaders for cross-cutting decisions, and to whom to delegate. Senior executives also serve the critical functions of role-modeling a culture of collaboration and of making sure junior leaders take ownership of the delegated decisions.

Big bets

Bet-the-company decisions—from major acquisitions to game-changing capital investments—are inherently the most risky. Efforts to mitigate the impact of cognitive biases on decision making have, rightly, often focused on big bets. And that’s not the only special attention big bets need. In our experience, steps such as these are invaluable for big bets:

  • Appoint an executive sponsor. Each initiative should have a sponsor, who will work with a project lead to frame the important decisions for senior leaders to weigh in on—starting with a clear, one-sentence problem statement.
  • Break things down, and connect them up. Large, complex decisions often have multiple parts; you should explicitly break them down into bite-size chunks, with decision meetings at each stage. Big bets also frequently have interdependencies with other decisions. To avoid unintended consequences, step back to connect the dots.
  • Deploy a standard decision-making approach. The most important way to get big-bet decisions right is to have the right kind of interaction and discussion, including quality debate, competing scenarios, and devil’s advocates. Critical requirements are to create a clear agenda that focuses on debating the solution (instead of endlessly elaborating the problem), to require robust prework, and to assemble the right people, with diverse perspectives.
  • Move faster without losing commitment. Fast-but-good decision making also requires bringing the available facts to the table and committing to the outcome of the decision. Executives have to get comfortable living with imperfect data and being clear about what “good enough” looks like. Then, once a decision is made, they have to be willing to commit to it and take a gamble, even if they were opposed during the debate. Make sure, at the conclusion of every meeting, that it is clear who will communicate the decision and who owns the actions to begin carrying it out.

An example of a company that does much of this really well is a semiconductor company that believes so much in the importance of getting big bets right that it built a whole management system around decision making. The company never has more than one person accountable for decisions, and it has a standard set of facts that need to be brought into any meeting where a decision is to be made (such as a problem statement, recommendation, net present value, risks, and alternatives). If this information isn’t provided, then a discussion is not even entertained. The CEO leads by example, and to date, the company has a very good track record of investment performance and industry-changing moves.

It’s also important to develop tracking and feedback mechanisms to judge the success of decisions and, as needed, to course correct for both the decision and the decision-making process. One technique a regional energy provider uses is to create a one-page self-evaluation tool that allows each member of the team to assess how effectively decisions are being made and how well the team is adhering to its norms. Members of key decision-making bodies complete such evaluations at regular intervals (after every fifth or tenth meeting). Decision makers also agree, before leaving a meeting where a decision has been made, how they will track project success, and they set a follow-up date to review progress against expectations.

Big-bet decisions often are easy to recognize, but not always (Exhibit 3). Sometimes a series of decisions that might appear small in isolation represent a big bet when taken as a whole. A global technology company we know missed several opportunities that it could have seized through big-bet investments, because it was making technology-development decisions independently across each of its product lines, which reduced its ability to recognize far-reaching shifts in the industry. The solution can be as simple as a mechanism for periodically categorizing important decisions that are being made across the organization, looking for patterns, and then deciding whether it’s worthwhile to convene a big-bet-style process with executive sponsorship. None of this is possible, though, if companies aren’t in the habit of isolating major bets and paying them special attention.

A belated heads-up means you are not recognizing big bets.

Cross-cutting decisions

Far more frequent than big-bet decisions are cross-cutting ones—think pricing, sales, and operations planning processes or new-product launches—that demand input from a wide range of constituents. Collaborative efforts such as these are not actually single-point decisions, but instead comprise a series of decisions made over time by different groups as part of an end-to-end process. The challenge is not the decisions themselves but rather the choreography needed to bring multiple parties together to provide the right input, at the right time, without breeding bureaucracy that slows down the process and can diminish the decision quality. This is why the common advice to focus on “who has the decision” (or, “the D”) isn’t the right starting point; you should worry more about where the key points of collaboration and coordination are.

It’s easy to err by having too little or too much choreography. For an example of the former, consider the global pension fund that found itself in a major cash crunch because of uncoordinated decision making and limited transparency across its various business units. A perfect storm erupted when different business units’ decisions simultaneously increased the demand for cash while reducing its supply. In contrast, a specialty-chemicals company experienced the pain of excess choreography when it opened membership on each of its six governance committees to all senior leaders without clarifying the actual decision makers. All participants felt they had a right (and the need) to express an opinion on everything, even where they had little knowledge or expertise. The purpose of the meetings morphed into information sharing and unstructured debate, which stymied productive action (Exhibit 4).

Too many cooks get involved in the absence of processes for cross-cutting decisions.

Whichever end of the spectrum a company is on with cross-cutting decisions, the solution is likely to be similar: defining roles and decision rights along each step of the process. That’s what the specialty-chemicals company did. Similarly, the pension fund identified its CFO as the key decision maker in a host of cash-focused decisions, and then it mapped out the decision rights and steps in each of the contributing processes. For most companies seeking enhanced coordination, priorities include:

  • Map out the decision-making process, and then pressure-test it. Identify decisions that involve a cross-cutting group of leaders, and work with the stakeholders of each to agree on what the main steps in the process entail. Lay out a simple, plain-English playbook for the process to define the calendar, cadence, handoffs, and decisions. Too often, companies find themselves building complex process diagrams that are rarely read or used beyond the team that created them. Keep it simple.
  • Run water through the pipes. Then work through a set of real-life scenarios to pressure-test the system in collaboration with the people who will be running the process. We call this process “running water through the pipes,” because the first several times you do it, you will find where the “leaks” are. Then you can improve the process, train people to work within (and, when necessary, around) it, and confront, when the stakes are relatively low, leadership tensions or stresses in organizational dynamics.
  • Establish governance and decision-making bodies. Limit the number of decision-making bodies, and clarify for each its mandate, standing membership, roles (decision makers or critical “informers”), decision-making protocols, key points of collaboration, and standing agenda. Emphasize to the members that committees are not meetings but decision-making bodies, and they can make decisions outside of their standard meeting times. Encourage them to be flexible about when and where they make decisions, and to focus always on accelerating action.
  • Create shared objectives, metrics, and collaboration targets. These will help the persons involved feel responsible not just for their individual contributions in the process, but also for the process’s overall effectiveness. Team members should be encouraged to regularly seek improvements in the underlying process that is giving rise to their decisions.

Getting effective at cross-cutting decision making can be a great way to tackle other organizational problems, such as siloed working (Exhibit 5). Take, for example, a global finance company with a matrix of operations across markets and regions that struggled with cross-business-unit decision making. Product launches often cannibalized the products of other market groups. When the revenue shifts associated with one such decision caught the attention of senior management, company leaders formalized a new council for senior executives to come together and make several types of cross-cutting decisions, which yielded significant benefits.

When you are locked in silos, you are unlikely to collaborate effectively on cross-cutting decisions.

Delegated decisions

Delegated decisions are far narrower in scope than big-bet decisions or cross-cutting ones. They are frequent and relatively routine elements of day-to-day management, typically in areas such as hiring, marketing, and purchasing. The value at stake for delegated decisions is in the multiplier effect they can have because of the frequency of their occurrence across the organization. Placing the responsibility for these decisions in the hands of those closest to the work typically delivers faster, better, and more efficiently executed decisions, while also enhancing engagement and accountability at all levels of the organization.

In today’s world, there is the added complexity that many decisions (or parts of them) can be “delegated” to smart algorithms enabled by artificial intelligence. Identifying the parts of your decisions that can be entrusted to intelligent machines will speed up decisions and create greater consistency and transparency, but it requires setting clear thresholds for when those systems should escalate to a person, as well as being clear with people about how to leverage the tools effectively.

It’s essential to establish clarity around roles and responsibilities in order to craft a smooth-running system of delegated decision making (Exhibit 6). A renewable-energy company we know took this task seriously when undergoing a major reorganization that streamlined its senior management and drove decisions further down in the organization. The company developed a 30-minute “role card” conversation for each manager to have with his or her direct reports. As part of this conversation, managers explicitly laid out the decision rights and accountability metrics for each direct report. This approach allowed the company’s leaders to decentralize their decision making while also ensuring that accountability and transparency were in place. Such role clarity enables easier navigation, speeds up decision making, and makes it more customer focused. Companies may find it useful to take some of the following steps to reorganize decision-making power and establish transparency in their organization:

Drawn-out and complicated processes often mean more delegating is needed.
  • Delegate more decisions. To start delegating decisions today, make a list of the top 20 regularly occurring decisions. Take the first decision and ask three questions: (1) Is this a reversible decision? (2) Does one of my direct reports have the capability to make this decision? (3) Can I hold that person accountable for making the decision? If the answer to these questions is yes, then delegate the decision. Continue down your list of decisions until you are only making decisions for which there is one shot to get it right and you alone possess the capabilities or accountability. The role-modeling of senior leaders is invaluable, but they may be reluctant. Reassure them (and yourself) by creating transparency through good performance dashboards, scorecards, and key performance indicators (KPIs), and by linking metrics back to individual performance reviews.
  • Avoid overlap of decision rights. Doubling up decision responsibility across management levels or dimensions of the reporting matrix only leads to confusion and stalemates. Employees perform better when they have explicit authority and receive the necessary training to tackle problems on their own. Although it may feel awkward, leaders should be explicit with their teams about when decisions are being fully delegated and when the leaders want input but need to maintain final decision rights.
  • Establish a clear escalation path. Set thresholds for decisions that require approval (for example, spending above a certain amount), and lay out a specific protocol for the rare occasion when a decision must be kicked up the ladder. This helps mitigate risk and keeps things moving briskly.
  • Don’t let people abdicate. One of the key challenges in delegating decisions is actually getting people to take ownership of the decisions. People will often succumb to escalating decisions to avoid personal risk; leaders need to play a strong role in encouraging personal ownership, even (and especially) when a bad call is made.

This last point deserves elaboration: although greater efficiency comes with delegated decision making, companies can never completely eliminate mistakes, and it’s inevitable that a decision here or there will end badly. What executives must avoid in this situation is succumbing to the temptation to yank back control (Exhibit 7). One CEO at a Fortune 100 company learned this lesson the hard way. For many years, her company had worked under a decentralized decision-making framework where business-unit leaders could sign off on many large and small deals, including M&A. Financial underperformance and the looming risk of going out of business during a severe market downturn led the CEO to pull back control and centralize virtually all decision making. The result was better cost control at the expense of swift decision making. After several big M&A deals came and went because the organization was too slow to act, the CEO decided she had to decentralize decisions again. This time, she reinforced the decentralized system with greater leadership accountability and transparency.

Top-heavy processes often mean more delegating is needed.

Instead of pulling back decision power after a slipup, hold people accountable for the decision, and coach them to avoid repeating the misstep. Similarly, in all but the rarest of cases, leaders should resist weighing in on a decision kicked up to them during a logjam. From the start, senior leaders should collectively agree on escalation protocols and stick with them to create consistency throughout the organization. This means, when necessary, that leaders must vigilantly reinforce the structure by sending decisions back with clear guidance on where the leader expects the decision to be made and by whom. If signs of congestion or dysfunction appear, leaders should reexamine the decision-making structure to make sure alignment, processes, and accountability are optimally arranged.


None of this is rocket science. Indeed, the first decision-making step Peter Drucker advanced in “The effective decision,” a 1967 Harvard Business Review article, was “classifying the problem.” Yet we’re struck, again and again, by how few large organizations have simple systems in place to make sure decisions are categorized so that they can be made by the right people in the right way at the right time. Interestingly, Drucker’s classification system focused on how generic or exceptional the problem was, as opposed to questions about the decision’s magnitude, potential for delegation, or cross-cutting nature. That’s not because Drucker was blind to these issues; in other writing, he strongly advocated decentralizing and delegating decision making to the degree possible. We’d argue, though, that today’s organizational complexity and rapid-fire digital communications have created considerably more ambiguity about decision-making authority than was prevalent 50 years ago. Organizations haven’t kept up. That’s why the path to better decision making need not be long and complicated. It’s simply a matter of untangling the crossed web of accountability, one decision at a time.

By Aaron De Smet, Gerald Lackey, and Leigh M. Weiss

Report: Digital Natives ‘Easily Duped’ by Information Online

Many students are having a hard time judging the credibility of online news, according to a new study from Stanford University. Researchers at the Stanford Graduate School of Education assessed middle, high school and college students on the their civic online reasoning skills, or “the ability to judge the credibility of information that floods young people’s smartphones, tablets and computers.”

The Stanford History Education Group recently released a report that analyzes 7,804 responses collected from students across 12 states and varying economic lines, including well-resourced, under-resourced and inner-city schools. To test news literacy, the researchers administered 56 tasks that involved open web searches. They found that when it comes to evaluating information that flows on social media channels like Facebook and Twitter, students “are easily duped” and have trouble discerning advertisements from news articles.

Native advertising, for example, “proved vexing for the majority of students,” according to the report. For one task, 203 middle school students were asked to evaluate the homepage of Slate magazine’s website. More than 80 percent of students believed that an advertisement with the words “sponsored content” was a news story. Several even responded that it was sponsored content, yet identified it as a credible news story.

Many people assume that today’s students – growing up as “digital natives” – are intuitively perceptive online. The Stanford researchers found the opposite to be true and urge teachers to create curricula focused on developing students’ civil reasoning skills. They plan to produce “a series of high-quality web videos to showcase the depth of the problem” that will “demonstrate the link between digital literacy and citizenship,” according to the report.

The report, “Evaluating Information: The Cornerstone of Civic Online Reasoning,” can be found here.

Facebook, Apple, Google Executives Push STEM at Trump’s Tech Meeting

Sheryl Sandberg, COO of Facebook, and Tim Cook, CEO of Apple, alongside a dozen other executives of major tech companies, met with Republican president-elect Donald Trump Wednesday to discuss jobs and the economy.

What ever happened after this meeting? Has any of these companies actually changed what they are/were doing?

Image Credit: Quartz.

Trump was relatively quiet about his plans for education while campaigning, but during the sit-down meeting at Trump Tower in New York City, a conversation about STEM (science, technology, engineering and math) education unfolded.

According to various reports, invitations were also extended to:

  • Jeff Bezoz, Amazon CEO;
  • Safra Katz, Oracle CEO;
  • Alex Karp, Palantir CEO;
  • Elon Musk, Tesla CEO and product architect;
  • Satya Nadella, Microsoft CEO;
  • Larry Page, Alphabet CEO and Google co-founder;
  • Eric Schmidt, Alphabet executive chairman and former Google CEO;
  • Chuck Robbins, Cisco CEO; and
  • Ginni Rometty, IBM CEO.

Peter Thiel, founder of PayPal and other companies and a member of Trump’s transition team, was also in attendance and sat next to the president-elect. Notably, Twitter CEO Jack Dorsey was not at the meeting.

Recode reported that meeting attendees talked about developing fairer trade deals and creating jobs, emphasizing the importance of innovative technologies, like automation and advanced manufacturing. Cook brought up President Obama’s work to advance STEM education in K–12, including national computer science initiatives, stressing STEM’s impact on the U.S. economy. Additionally, Sandberg pushed the importance of STEM education for women and underrepresented minorities in the tech industry.

 

K12 and other Virtual Companies REJECT ACCOUNTABILITY/TRANSPARENCY Proposal

Virtual charter school company K12 Inc. rejected a transparency proposal Thursday that would have required the company’s board of directors to create a new report detailing K12’s lobbying efforts.

The proposal came from a group of shareholders, represented by Arjuna Capital, who said the company spends millions on state lobbying, even as its stock has been dropping and revenues have decreased.

K12 Inc. has spent at least $10.5 million to hire lobbyists in 21 states, according to more than a decade of state lobbying disclosure forms examined by Education Week as part of a recent investigation into the lobbying efforts of for-profit virtual charter school operators.

The shareholders called on the company’s board to prepare an annual report detailing spending on “direct or indirect lobbying or … grassroots lobbying communications.” They also wanted the company to report K12’s membership in, and payments to, any tax-exempt organization that writes and endorses model legislation — such as the American Legislative Exchange Council.

The K12 shareholder effort to push for more transparency was headed by Bertis Downs, the legal counsel for the rock group R.E.M. as well as a traditional public school parent and advocate in Athens, GA.

Downs also sits on the board of the Network for Public Education, the group co-founded by education historian and traditional public schools advocate Diane Ravitch.

K12’s board of directors opposed the proposal. In a proxy statement put out ahead of the annual shareholder’s meeting, the board said the requirements outlined in the proposal are not necessary and could hurt the company.

“The expanded disclosure requested by this proposal could place the company at a competitive disadvantage by revealing strategies and priorities designed to protect the economic future of the company, its stockholders and employees,” the statement said.

K12 has faced major challenges in recent years. Revenues are down by $75 million from last year, according to an Education Week report. Investors sued the company in 2014, claiming it had misled them before its stock prices fell in 2013. A federal judge dismissed the suit last year.

And California Attorney General Kamala Harris launched an investigation into the company for alleged false advertising and unfair business practices. In July, K12 Inc. agreed to pay $8.5 million to settle the state’s claims and provide $160 million in balanced budget credits to the nonprofit schools it manages, including California Virtual Academies.

Despite those setbacks, the company continues to open new schools in states such as Alabama, Maine and North Carolina.

 

by Richard Chang

Could a robot be grading your homework?

Artificial intelligence has become an increasingly big issue for education – not least because many tech companies and publishers are circling around the huge commercial opportunities. Especially with the possibility of the new chief at the USDOE coming on board soon.

One of those companies is Vantage Learning the industry leader in Artificial Intelligence and Cognitive Computing Technologies. They were the first company to reach human level accuracy in their scoring engine and have patents on the world’s best artificial intelligent engine (Intellimetric) that automatically scores essays and provides prescriptive feedback to students globally.

To date the engine has scored more than 125,000,000 essays including many large-scale essays such as the GMAT, MCAT, SAT and ACT to name a few.

When thinking about the bigger picture in education though, could students really get their answers from a robot rather than a teacher? They are already receiving prescriptive feedback, and having their papers scored more efficiently than teachers can currently score. This leaves more time for intervention, content acquisition and remediation.

Donald Clark said it was a mistake to think jobs in education would not be automated, and I agree although, if technology can replace the teacher, then it should as that teacher is not doing their job, because teaching is more than technology and scores. It is about passion, choice and shaping our future as a country. You can decide for yourself and read this article. (http://www.edudemic.com/education-technology-pros-cons/)

Dr Tarek Besold, speaking at an educational technology conference in Berlin, said a joke-writing computer showed how robots could be creative as well as carrying out repetitive, factory-floor tasks.

And he highlighted experiments already taking place in using artificial intelligence in teaching.

Digital teacher

This summer, Georgia Tech, a university in Atlanta in the US, deployed a teaching assistant called Jill Watson for one of its postgraduate courses.

Except that Jill Watson was really a robot, which helped students and answered their questions in an online forum, without revealing her cyber-identity.

The only thing that students noticed was that Jill Watson answered questions and provided feedback much more quickly than other teaching assistants.

Dr Besold, from Bremen University, said such robotic teachers were becoming increasingly sophisticated and had advantages over human teachers. I am still wary of this as a model, being a teacher I know the reality of what it takes to be a teacher and a pseudo-parent at times.

They were always ready to respond, they were never bored, tired or distracted.

But such clever computers could also be stupid.

While they could be trained to operate for a particular task or set of questions, they couldn’t easily adapt that knowledge to a different setting.

For example; Peter Murphy, the CEO of Vantage Labs said “a human who was good at chess would be likely to be able to play other games that required a complex thought process; while a chess computer would struggle, unless it had been specifically programmed. This also holds true for the computer that beat the Japanese strategy game “Go” as well”.

Will robotics and automation take more professional jobs?

There are also more subtle questions about online help from a robot. Would you feel the same about positive feedback if it came from a machine rather than a person?

What about the pastoral side of teaching? Could a robot offer empathy as well as factual insights?

And academic instruction is often not about “right” or “wrong” answers, but teaching how to think and investigate. It is about teaching critical thinking and empathy. Can a robot or cognitive computing engine actually perform these tasks of teaching or leading students to critically think and problem solve?

Destroying jobs

Donald Clark, a professor at Derby University and an education technology entrepreneur, said it was a mistake for anyone to think that education would be exempt from the impact of automation.

“Are we really saying that accountants, lawyers and managers can all be replaced by artificial intelligence – but not teachers?”

Can a robot truly appreciate a creative student’s answers?

Clark argued that artificial intelligence would change office jobs and professions in the way that automation had already transformed production lines.

“Artificial intelligence will destroy jobs – so why not use it for a social good such as learning?” he asked.

The acceleration of big data and more powerful computer systems meant that more and more sophisticated tasks could be automated, said Prof Clark.

It is already ebbing around the edges of education.

Online tutors

The name of Georgia Tech’s robot teacher – Jill Watson – is a reference to the underlying Watson computer system, developed by IBM to answer questions in ordinary language.

The Watson system is also being used in an experimental project from education companies. There has been AI used in education by Vantage Learning for the past 15 years and they developed the first automated scoring engine to reach human level accuracy. (http://www.vantagelearning.com)

The use of artificial intelligence is growing in the workplace.

It’s not going to replace a conventional teacher, but it’s an indication of how online courses and revision tutorials could develop, with testing and feedback all wrapped up together.

But there are skeptics who see this as another wave of technology over-promising.

“We’ve been here before – with radio, television, computers, the internet,” said Stavros Yiannouka, chief executive of the Wise project, run by the Qatar Foundation.

“Technology in itself doesn’t revolutionize anything,” he said. Change in education is driven by public policy decisions, he said, not computer software.

There are also questions about whether automation will create a social divide – with stripped down, low cost, semi-automated courses, for those who cannot afford a traditional taught course.

Entrepreneur Nell Watson said that despite describing herself as a “happy clappy evangelist” for artificial intelligence, the role of teacher would not be replicated by a robot.

Cultivating the whole person and helping them to “blossom” was not something that was going to be achieved by an algorithm, she said.

And she doubted whether a computer could appreciate the work of an innovative student who thought outside the conventional questions and answers.

But automation is advancing.

The Bank of England’s governor, Mark Carney, said this month that 15 million jobs in the UK could be automated, including middle-class professions.

Changes in technology would “mercilessly” destroy jobs, he said.

So could it be “Goodbye Mr. Chips” and “Hello Mr. Silicon Chips”?

For more information on Artificial Intelligence, Cognitive Computing or Natural Language Understanding reach out to me, I am always looking to discuss the future of the world we live, play and work in.

Ka’Ching! 2016 US Edtech Funding Totals $1 Billion

This is a repost of an article that appeared on EdSurge

Santa proved a little more parsimonious to U.S. edtech companies, which altogether raised an estimated $1.03 billion across 138 venture deals in 2016. Those tallies dipped from 2015, which saw 198 deals that totalled $1.45 billion. (Or, from a different perspective, U.S. edtech companies raised roughly 57 percent of what Snapchat did in its $1.8 billion Series F round.)

In this annual analysis, EdSurge counts all investments in technology companies whose primary purpose is to improve learning outcomes for all learners, regardless of age. This year startups that serve primarily the K-12 market raised $434 million; those targeting the postsecondary and corporate learning sector raised $593 million.

Since 2010, venture funding dollars for U.S. edtech startups have increased every consecutive year. It’s worth noting that even though 2016 marked the end of this trend, the dollar total still surpasses the years before 2015.

The downturn isn’t specific to the education industry but rather reflects a broader slowdown across all technology sectors, says Tory Patterson, managing partner at Owl Ventures. “There’s a broader shift in venture capital where there’s less exuberance companies that haven’t really nailed the business model,” he tells EdSurge.

Dealflow dips has also been felt in the health, real estate, construction and financial technology sectors. Across the globe, venture deals returned to 2014 levels, according to CB Insights. The market uncertainty has led some high-profile companies to hit pause on bigger plans. SoFi, which offers loans and other student services, pushed back plans for its initial public offering this year. Pluralsight, an online learning company that was also expected to IPO, is also on hold.

Venture-backed startups tend to swing between two spectrums, says Amit Patel, a partner at Owl Ventures. On one end are businesses “that grow aggressively but have no revenue associated. The other are those laser focused on business model and revenue. The mood is swinging towards the latter.”

Commitments to “impact” or “mission” aside, all investors—even in education—want to see returns. Often that means converting users into dollars.

“We’ve noticed VCs becoming more selective about their education investments, asking more questions about revenue growth and the leading indicators of product adoption, implementation timelines and ultimately usage,” says Jason Palmer, a general partner at New Markets Venture Partners. Unlike Instagrams and other “5-year consumer internet hits,” more investors, according to Palmer, now realize “it can take 10 or 15 years to build a sustainable education business.”

Breaking Down the Numbers

As in previous years, companies offering tools in the postsecondary and “other” categories out-raised other products. (“Other” includes a mix of products that help business professionals develop skills, are aimed at parents, or are not used in K-12 or higher-ed institutions.)

Expect this trend to continue, says Palmer, as investors come to “a greater recognition that higher education institutions adopt and implement more rapidly than K-12 [schools].” Tuition dollars may be one reason why they have adopted technologies such as student retention and predictive analytics platform. “Colleges and universities are facing financial pressures to keep students who contribute to their revenues. In K-12, you don’t have the same urgency of students as revenue drivers,” he suspects.

This year saw no mega-rounds for startups in the postsecondary sector—unlike 2015, which saw HotChalk, Udacity, Udemy, Coursera and Civitas Learning account for more than $520 million of funding. (Udemy did lead this pack in 2016 with a $60 million round.)

In fact, the biggest funding round of 2016 for a U.S.-based startup went to Age of Learning, which raised $150 million and accounts for 55 percent of the funding total for K-12 curriculum products. The Glendale, Calif.-based company is the developer of ABCmouse, a collection of online learning activities aimed for young children. First developed for the consumer and parent market, the tool is attempting to make headway into schools and classrooms.

Choosier Angels

Angel and seed level funding rounds, which signal investors’ interest in promising but unproven ideas, saw a small decline as well. The 66 deals at this stage are the lowest since 2011, although they totaled $62.5 million—roughly on par with 2014 levels.

Over the past five years, the average value of seed rounds has been increasing, from around $600K in the early years of this decade to roughly $1 million in 2015 and 2016. Discounting edtech accelerators, which typically invest $20K to $150K in startups, the 2016 seed round average actually surpasses $2 million. (We counted 28 such publicly disclosed seed rounds totaling $60.2 million)

Fewer but bigger seed deals are “a sign of maturation in the industry,” says Shauntel Poulson, a general partner at Reach Capital. Unlike previous years, where upstarts and ideas popped up the market, she believes the market is currently in a “stage of consolidation where leaders and proven ideas are emerging.”

Aspiring entrepreneurs ought to pay heed. What this means is that “the bar for seed rounds is getting higher,” Poulson adds. “Before it was about a promising idea and a great team. Now you need to show more traction and even some revenue.” Over the past few years investors have learned that “it’s best to focus on business model sooner rather than later.”

Palmer believes the days where startups could raise money before making some may be over. Expect to get grilled over “revenue growth, product adoption, implementation timelines and ultimately usage,” he says. To round out the questions, “VCs are also starting to ask about product efficacy.”

Looking Ahead

Unsurprisingly, investors held a cheery outlook for 2017, expecting funding totals to hold steady or even increase. More companies will be able to demonstrate sustainable revenue, predicts Owl Ventures’ Tory Patterson, and in turn woo investors’ appetite. “We think a lot of companies will be able to hit the $10 million revenue milestone.”

Emerging technologies such as artificial intelligence, augmented and virtual reality could drive further investments as their applications to help improve learning outcomes become clearer. Also expect to see Chinese investors paying closer attention, says Poulson. “There’s a big after-school market [in China] and an opportunity to leverage a lot of the content that’s being developed in the U.S.”

There’s also word on the street that several education-focused venture firms have re-upped their coffers with new funds to support proven, maturing startups. Stay tuned for more details.

Disclosure: Owl Ventures and Reach Capital are investors in EdSurge

The Tragedy of Student Loans

 

One of the big scams going around right now is student loans for individuals attending for-profit universities. It goes something like this: Heavy advertising for pain free, at-your leisure online or on-site degrees—encouraging students to take on a large debt load to pay for their studies—and then frequently little (if any) support for students, inadequate classes, and difficulty transferring credits to other institutions. The dropout rate is typically substantial. Personal student debt is growing at a staggering rate.

Here’s the thing though—students at for-profit institutions represent only 9% of all college students, but receive roughly 25% of all federal Pell Grants and loans, and are responsible for 44% of all student loan defaults.

study by The National Bureau of Economic Research, in Cambridge, Massachusetts, suggested that students who attend for-profit education institutions are more likely to be unemployed, earn less, have higher debt levels, and are more likely to default on their student loans than similar students at non-profit educational institutions. Although for-profits typically serve students who are poorer or more likely to be minorities, these differences do not explain the differences in employment, income, debt levels, and student loan defaults. The Government Accountability Office has also found that graduates of for-profits are less likely to pass licensing exams, and that poor student performance cannot be explained by different student demographics.

For-profits have higher completion rates for one- and two-year associate’s degree programs, but higher dropout rates for four-year bachelor’s degrees. However, studies have suggested that one- and two-year programs typically do not provide much economic benefit to students because the boost to wages is more than offset by increased debt. By contrast, four-year programs provide a large economic benefit.

An investigation by the New York Times suggested that for-profit higher education institutions typically have much higher student loan default rates than non-profits. Two documentaries by Frontline have focused on alleged abuses in for profit higher education.

The following infographic from Collegestats.org will give you a good visual of what’s going on with student debt. Call me old-fashioned, but I’ve always thought that the fundamental purpose of an educational institution should be to educate, not to turn a profit.

 

The Tragedy of Student Loans

What Did 2013 Hold for Educational Technology in Schools

Looking back at the article I was astounded to find that basically none of the information in the first chart was relevant and the proposal that “Apps” would be the prevalent part of the year actually was/is true. 
via Smartblogs/Katharine Haber

To connect with those working on the front lines of education technology, SmartBrief on EdTech editor Katharine Haber asked readers about their thoughts on what 2013 will bring for technology in schools.

According to our results, about one-third of respondents see classroom technology as the most significant issue on the horizon, while a slightly smaller group is concerned about online education, followed by computer-based testing and digital citizenship.

When asked how their schools and districts are using technology to enhance student learning, a majority of respondents reported that some teachers are employing tech tools in the classroom, while a significantly smaller proportion said technology is playing a broader role throughout the curriculum or being integrated through blended-learning programs or “bring your own technology” programs.

Readers reported that online applications and games are the most effective tools for engaging students, while digital textbooks and resources, along with mobile devices, are not far behind.

Interestingly, few respondents see social media as an effective tool. Given the ongoing buzz about Facebook, Twitter and Instagram, this response begs the question of whether many schools simply are not using social media as part of classroom instruction.

There are arguably numerous factors to consider when using social media with students, and many schools and districts might be blocking or otherwise prohibiting use of such websites on campus. However, given their popularity, is it possible there is an untapped resource here? What do you think?

What do you see as the most significant issue in education technology for 2013?

Technology in the classroom

33.88%

Online education

25.62%

Computer-based testing

21.49%

Digital citizenship

19.01%

Which statement best describes how your school or district is integrating technology into student learning?

Some teachers use tech tools as part of classroom lessons

63.78%

Technology is integrated throughout the curriculum

19.69%

Our school/district has a bring-your-own-device policy

8.66%

Our school/district employs blended learning

7.87%

Which tech tools most effectively engage students in your classroom, school or district?

Online apps and games

40%

Digital textbooks and resources

28.89%

Mobile devices

27.78%

Social media

3.33%

Katharine Haber is an associate editor for SmartBrief, writing and editing content about a variety of topics in education.

Great Post by David Warlick

via 2¢ Worth

Today’s infographic is simple and to the point. A big part of grade school and even college and onward, is writing papers. Some professions write more papers than others, but it is still an important skill in order to get your point across. This infographic uses venn diagrams to convey the importance of different parts of papers, and to show how they interact with one another. It also shows how much of your paper should include each part.

Of course every paper should begin with an introduction and end with a conclusion. It should also include several point in the middle, that are introduced and concluded in the introduction and conclusion. But how should the middle be laid out? That is up to the author, but it should there is a bit of a formula.

This infographic does a great job of showing that there should be pros and cons. You should always share how your paper may be argued against, and go ahead and prove some of these points wrong. In addition, a good paper should show why the information is important. Why should someone read your paper?

Show this to your students whenever a paper is assigned. Make sure your students are ready to write a good paper, and know what is involved in writing such a paper.

 

write-your-paper-right

http://visual.ly/write-your-paper-right

How to Support Teachers for 21st Century Learning

via eClassroom News

Experts weigh in on how administrators can support teachers in implementing collaboration and creativity

Implementing broad concepts like critical thinking and communication may seem like natural next steps to educators, but unless teachers receive support from school policy and infrastructure, providing students with a true 21st century education may not be so easy.

This was a key topic of discussion during a recent Connected Educator Month webinar, hosted by the Partnership for 21st Century Skills (P21) and EdLeader21—a national network of school and district leaders focused on integrating the 4Cs into education.

The 4Cs–communication, collaboration, critical thinking, and creativity–are part of P21’s mission to help educators teach students 21st century skills. Webinar panelists said this task can’t be accomplished without support from school administrators in the way of space design, instructional practices, and school policy.

Dana Strother, chief academic officer at Douglas County School District in Colorado, said her district “looked at Bloom’s Taxonomy and vetted our state’s standards through the taxonomy” during an evaluation of instructional practice.

“Areas that were lacking we improved through what we call ‘World Class Outcomes,’ and instructional design that allows for the 4Cs. We also provided CIA curriculum and instruction alignment and wove authentic learning experiences into the curriculum for support,” she said.

The district also made it a priority to provide supporting infrastructure through district policy on risk-opportunities.

“It’s important to let teachers know, in various ways, but also through policy, that we support risk-taking opportunities, or new strategies, projects, or professional development opportunities that may be new or unique,” she said.

For example, Douglas County lets teachers experience inquiry-based professional development opportunities in order for teachers to learn through the same practices they’re expected to teach students.

“We’re asking teachers to incorporate new kinds of teaching that include the 4Cs, so why should teachers in turn be taught in a different manner? Sometimes by thinking outside of the box and going against traditional methods, especially from an administrator standpoint, the results are better,” Strother said.

Randy Fielding, chairman and founding partner of educational facilities planning and architectural design firm Fielding Nair International, said he believes school design also factors heavily into incorporating the 4Cs into a student’s daily life.

Fielding’s design firm tries to incorporate 20 “learning modalities” into school design, which include concepts, such as Independent Study, Peer Tutoring, Team Collaboration, and One-on-One Learning, to support the 4Cs of instruction.

“To have a truly 21st-century school, you have to inspire organic collaboration, critical thinking, creativity, and communication, and focusing on design can help.”

“To have a truly 21st-century school, you have to inspire organic collaboration, critical thinking, creativity, and communication, and focusing on design can help. For example, you could have a ‘watering hole’ space off hallways where students could casually converse; you could have a ‘cave space’ where students could reflect for independent thinking; and you could have a ‘campfire space’ where everyone gathers to collaborate,” Fielding said.

Panelists emphasized that it’s also important for administrators and teachers to understand that instruction focused on the 4Cs doesn’t just work for certain kinds of subjects, students, or teachers.

“The 4Cs work for every kind of student and teacher in classrooms across the country,” said Donna Harris-Aikens, director of Education Policy and Practice at the National Education Association (NEA). “It’s less a series of requirements and more just authentic learning. For example, a math class could use its English and design skills to help draft a proposal to help senior citizens in their community make their homes more accessible. For this kind of project, you need the 4Cs in STEM, English, and community service.”

Fielding said it’s important that school and district leaders support teachers in working together to develop collaborative projects for their students.

One of the schools his firm works with has a student-run lunch program through which students negotiate with local farmers. They serve the week’s menu selections on carts around the school so students can taste-test their creations. Students in the program generate quarterly reports on profit and loss, and send those reports off to the school board.

“Students get credit for working in this program, which essentially teaches them collaboration skills, analytical skills, and even creative skills, thanks to cooking,” he said.

However, panelists said that there are still barriers for teachers who want to pursue the 4Cs, including getting first-world experience on how to actually teach broad concepts like creativity.

“That’s why we introduced the Creative Innovator Network in our district, which allows teachers to collaborate with not only their peers on different projects, but also local businesses to brainstorm ideas on how students can better serve the community,” said Strother. “We also bring students into the teacher professional development sessions to hear their voice and how they enjoy learning, so that teachers can adapt their instruction.”

“The biggest barrier for teachers is time,” said Harris-Aikens. “Finding time to make everything work effectively and collaborate is hard, especially because planning, or collaborating, time needs to be on a consistent and continual basis. Students also need a large amount of time to work on these projects, and to have time flexibility in case they make mistakes, as well. Administrators need to make sure teachers and students can have that time in their day.”

For more on this topic, watch the full webinar.