Digital transformation means different things to different departments, according to new research out of Deloitte LLP. Marketing, sales, customer service and even finance often see digital as customer-facing tools and applications. But that’s only the tip of the iceberg, according to Deloitte.
“What many business leaders currently regard as ‘digital’ is predominately the part of the iceberg that shows above water,” states the Navigating legacy: Charting the course to business value report. “What lies below is often legacy systems, a rigid organizational culture, and antiquated processes that have encumbered the shift toward digital.”
The Deloitte researchers encourage CIOs, whom they describe as being best positioned to see the entire iceberg, to step up and help get everyone on the same page. In that vein, here’s how two CIOs, who took part in Deloitte’s research, define digital at their companies.
Cause and effect
Vittorio Cretella, CIO at Mars Inc. in McLean, Va., defines digital in terms of cause and effect. The causes include massive amounts of data, the consumerization of IT and the availability of more computational power thanks to the cloud.
The combination of data and technology affects not just “the digitization of commerce,” Cretella said, “but also the digitization of operations.” For that reason, the business model of Mars, a company founded in 1911, is changing to take advantage of digital technologies. He is currently looking at artificial intelligence technology, including robotic process automation and cloud services from IBM Watson, to automate business processes. Technologies like these will also help to democratize analytics by “spreading knowledge across the company that allows our talented associates to make faster decisions and better educated decisions,” Cretella said.
So, when he talks about the concept of digital, he makes sure to talk about the digitization of commerce, of operations and of the business model. “It touches all sides of the business,” he said.
Knocking down silos
At NuVasive Inc., a medical device manufacturer aiming to make spine surgeries less invasive, digital is the lifeblood of it business model.
“Digital doesn’t just mean we’re going to put a website up,” said Johnson Lai, CIO at the San Diego, Calif.-based NuVasive. “Digital means the entire flow, all of the way through the organization and looping that back around to a commercial goal.”
NuVasive’s digital-based business model, which includes applications and digital platforms, requires IT and the business to work closely together. “Those conversations and decisions are becoming so depending on each other and each other’s function, that I think all C-level individuals are now knowledgeable in each other’s silos, so to speak,” he said.
The new reality means it’s not unheard of for the CFO to spend two days at an IT conference with Lai. And vice versa, if warranted, he said.
As vendors rake in revenues from software-as-a-service subscriptions, CIOs could see their SaaS costs rise 10% to 15%.
A new tech spending forecast from Forrester research advises CIOs to negotiate caps on price increases in cloud software agreements — and to evaluate alternatives to current vendors when contracts expire.
The problem, Forrester analyst Andrew Bartels said, is SaaS agreements are often structured “in ways that in fact don’t provide downward flexibility of costs — [they] only provide upward flexibility.”
So a contract with a vendor may allow for prices to rise as IT adds more users to an application, said Bartels, who wrote the report. What they don’t do is decrease if the number of users goes down. And many of those contracts last for three years.
There are other aspects of SaaS that box CIOs in on cost. When an organization owns the servers that its business software runs on, it can stop paying maintenance on it, for example, to save cash, Bartels said. Or it can decide not to do an upgrade. Not so with SaaS.
“Any time you’re using SaaS, any time you’re using cloud, you don’t have the option of stop paying because as soon as you stop paying, you lose the technology,” Bartels said “You’re renting it.”
Rising SaaS sales, SaaS costs
The attention to contract details and exit clauses is particularly important going forward, Bartels said. SaaS sales are expected to rise in 2017 despite uncertainty surrounding President-elect Donald Trump’s policies on international trade deals and immigration. But this is not the case for all tech sales. Indeed, the Forrester report lowered its pre-election forecast of 5.1% growth in tech spending to 4.3%, as companies remain cautious about investments.
Swelling SaaS sales reflect Forrester’s projection that sales of “business technology” — that is, technology that aims to serve and keep customers and win new ones — will also grow by 7.7% in 2017. In contrast, IT spending is expected to increase by 2.8%.
“The type of uncertainty that we’re facing becomes an incentive for firms to adopt cloud perhaps more rapidly than they might otherwise adopt it,” Bartels said. A heightened adoption rate of cloud sharpens the challenge for CIOs.
“One of the downsides of cloud technology is the potential — unless you are careful, unless you negotiate carefully, unless you create exit paths — that you’ll be trapped into agreements where your cost rises over time and doesn’t in fact either flatten out or go down in tough times as you might like it to,” Bartels said.
Chief data officers are gaining organizational clout, according to a new report from Gartner. Researchers at the consultancy found that companies are establishing a data office, what they refer to as “the office of the CDO,” complete with staffing, budget and specific responsibilities.
“This is a new business function, equal to IT and HR, finance, supply chain and any of the operations departments,” said Jamie Popkin, a Gartner analyst and co-author of the new research, which is based on interviews and online surveys with 180 chief data or analytics officers or others who hold a high-level data and analytics position.
The consultancy’s first survey of chief data officers was qualitative; the current report, Survey Analysis: The Second Gartner CDO Survey – The State of the Office of the CDO, is a quantitative study, with researchers looking to consider the merits of eight CDO hypotheses, including the organizational structure of the role itself.
“What we’re seeing is that, increasingly, there is an office of the chief data officer run by a chief data officer,” Popkin said. “And the chief data officer generally is having a very broad scope of responsibilities.” Because the position cuts across an organization, Gartner predicts CDOs will use the position to propel themselves into another C-level role in just three years.
The office of the CDO
Chief data officers are often brought in as governance gurus. The position was born out of the financial industry, in which companies have heavy compliance and regulatory requirements, Popkin said. Since its emergence in finance, companies such as those dealing with sensitive data or are transactional-heavy have also taken to the chief data officer role.
Researchers found that more than half of the respondents (54%) have a fully or partially implemented office of the CDO; another 20% are exploring or planning to implement one within the next year. The office of the CDO is still a relatively small one — no more than 24 people, according to 61% of respondents. But, as the report states, “with people and programs [come] budget.”
The average budget globally for the office of the CDO is $6.5 million, with North American companies budgeting more than twice the amount of their European counterparts.
The CDO’s unique perspective
Ensuring data quality, information strategy and master data management were and are primary responsibilities for CDOs, according to the research. But the potential impact a CDO has on the organization extends beyond keeping corporate data in order. Popkin said CDOs are uniquely positioned to be change agents and, as such, break out of the chief data officer role and into another influential C-level position.
Because they’re tasked with looking across the organization, CDOs understand how things operate, where there is resistance to change and why there’s resistance to change, and they can help groups change the way they do things, according to Popkin. They can shine a light on when and where a process or business model breaks down.
The experience they gain from helping transform an organization sets them up for future C-level positions such as a chief marketing officer, chief operations officer and even a chief executive officer. Indeed, Popkin and his co-researchers predict 15% of CDOs will begin to parlay their expertise into another C-level role by 2020. “I think someone who has that ability to work across all of the administrative functions is actually demonstrating the personal and professional maturity you might expect in a CEO,” Popkin said.
He pointed to the turnover they’re already seeing among the chief data officer role — not due to failure but due to demand — as a piece of evidence behind their thinking. “We think there are already bidding wars going on for top CDOs who have demonstrated their capability,” he said.
Hyper-converged systems are drawing a lot of interest. The main reason is simplicity. They bring together all the necessary data center components in one package — computation, storage, networking and virtualization. So the systems are easier to buy, implement and manage than traditional infrastructure. They take up a lot less room and can reduce management costs.
How can’t CIOs find an appeal? To determine whether hyper-converged systems are a good fit, they should start by asking a variety of questions.
Start with the basics
Consultant Judith Hurwitz said CIOs should consider specific uses — what do they actually want to do?
“Are you analyzing data in real time and coming up with next steps that really require a tremendous amount of compute and storage, where all of that has to come together very quickly?” said Hurwitz, president of Hurwitz & Associates and a prolific author of books on IT.
A cloud infrastructure service by say, Amazon Web Services or Microsoft’s Azure, could work, too, but depending on the applications that will be run, it could run up some serious bills.
“What is it going to cost you in the public cloud?” Hurwitz said.
Exactly what CIOs will do with a hyper-converged system is also important to John Burke, an analyst at Nemertes Research. CIOs need to think about what kind of performance they will need for the applications they will run — things like how many units of information need to be processed and how fast.
“You’ve always got to ask yourself the performance questions,” Burke said. “Will [a hyper-converged system] deliver the performance I need for the job that I envision running on it?”
CIOs should also think about where their administrators currently spend their time and how much time a hyper-converged system might save, he said.
Thinking of others
But CIOs can’t just ask themselves questions, Hurwitz said. They also need to pepper their constituents, their business users, with them.
“The basic question is, ‘What do you want to do that you can’t do now? What’s holding you back?'” Perhaps the business side wants to use applications that rely on the internet of things or on huge amounts of data or analytics — and their current infrastructure systems aren’t cutting it.
When they’re ready, Hurwitz said, CIOs need to take their concerns straight to the companies that sell hyper-converged systems.
“You put those same questions to those vendors: ‘This is what the people in my organization are trying to solve. Show me how you do it,'” she said.
Jeffrey Bornstein, SVP and CFO at General Electric Company, took time during his fireside chat at the MIT CFO Summit to make a distinction between what he called the “consumer internet” and the “industrial internet,” a term coined by GE that refers to industrial machine to machine communication.
“The architecture and the infrastructure of the industrial internet is completely different than the consumer internet,” he said. Rather than send all of the data to the cloud for analysis, the industrial internet relies on edge computing, the ability to collect and analyze data closer to the machine itself.
When a customer buys an item on Amazon, the transaction happens in seconds — not milliseconds, Bornstein said. And that’s because Amazon captures the data; sends it to the cloud; analyzes it; runs it against a profile it has of the customer; checks on the product’s digital twin, a digital representation of a physical asset; and then responds, according to Bornstein.
“When Amazon sends you back recommendations and you look at it, it takes you a couple of seconds to ingest it, and if you decide none of that is interesting, there’s no cost associated with that. There’s no cost for the false positive,” he said. “But in the industrial internet, the cost of a false positive could be catastrophic.”
A piece of industrial machinery like a jet engine, for example, needs to be able to respond to requests — such as a data anomaly — in microseconds rather than seconds, Bornstein said. Rather than send all of the data to the cloud and wait for a response, a good chunk of the data analysis needs to happen at edge — on or near the industrial machine itself.
“A very small amount of data will migrate all of the way to the cloud where you’ll do long-term data and analysis,” he said. But most of the compute happens where the machine lives.
There’s another reason for keeping compute local. “The amount of data we’re talking, just in our jet engine business, is way beyond anything Facebook or Google deals with,” he said. “So you’d never be able to pour all of that information to the cloud anyway.”
Donald Trump’s surprise win over Hillary Clinton in the recent U.S. presidential election spurred a lot of questions about the opinion polls leading up to Election Day and how they were conducted. Harvard University political scientist Gary King said the attention is focused on the wrong group.
“The story is not really about the pollsters; the story is really about the people,” said King, who also leads Harvard’s Institute for Quantitative Social Science.
Certainly, the campaigns turned up twist after twist — Clinton’s swoon at a 9/11 memorial service, seemingly giving credence to reports about her ill health; infighting among top brass in the Trump campaign; leaked Democratic National Committee emails indicating that officials conspired against Clinton’s primary challenger, Bernie Sanders; a surfaced 2005 video of Trump boasting about groping women.
Changing hearts and minds?
Opinion polls zigzagged — Clinton was up by a few percentage points, then she was up by a lot more, then the race tightened and it was tougher to call. Through it all, the media, King said, characterized voters as indecisive, favoring one candidate and then the other as pundits pontificated and “fake news” circulated on social media.
News website Politico asked pollsters about fluctuating polls before the Nov. 8 election and found that when there was bad news about, say, Trump, the Republican candidate, registered Republican voters were less likely to answer questions about the election. Ditto for news on Clinton and Democratic voters.
Voters themselves are remarkably stable, King said. They tend to choose early on whom to support and then move toward that choice throughout the campaign. (King co-wrote a paper on the tension between variable polls and predictable elections in 1993 and stands by it today.)
“If you watch CNN, they’re all obsessed about the people being swayed by this, and the people being swayed by this and they only talk about the horse race,” King said. “Very few people know people who flipped and flopped across the campaign.”
Once the voters get a general understanding of who candidates are and what their ideologies are, King said, forecasters can pretty reliably predict the outcome of the election, at around the times of the Republican and Democratic conventions, plus or minus three or four percentage points.
What happened in this election, he said, wasn’t that voters switched from planning to vote for Trump to Clinton and then back to Trump or vice versa. It was just that the race was incredibly close.
“The facts about people are that people are very stable and very predictable and in this sense trustworthy,” King said. “They’re not swayed by crazy little events in the campaign.”
Rising use of mobile phones means pollsters have to rethink how to run opinion polls during elections. Read about it in this SearchCIO news story.
Your organization launched a daring new product. It wants fast feedback from customers, so it signs with a company that does customer satisfaction surveys.
Quick survey: Would you trust the results?
It may seem that now — just weeks after political surveys and resulting analysis largely missed Donald Trump’s victory in the U.S. presidential election — is a bad time to ask. But with more organizations using data analysis to make critical business decisions, I’d argue it’s a great time to ask.
Harvard University political scientist Gary King said companies can learn a valuable lesson from what pollsters got wrong: If they want to buy services from a survey research outfit, they should ask tough questions about how it does its surveying.
“I would ask, ‘How do you know that you’re going to get a right answer?'” said King, who is also the director of Harvard’s Institute for Quantitative Social Science. “‘Give me some evidence that what you’re doing makes sense.'”
Beyond customer satisfaction surveying, survey research services include market research, to gather information about markets or customers, and new-product research, to determine whether a certain product or service will satisfy a certain need.
A serious problem with the political side of survey research today, King said, is this: Pollsters can’t easily get a representative sample of voters — that is, a small group of people who reflect the larger population. Lots of people use mobile phones only, and they often don’t want to respond to polls.
The nice thing about polling during elections is, after pollsters gather results of their survey — which point to one result or another — come Election Day, they learn the truth, King said.
“If the survey went wrong somehow or in some way small or large, then we get to know,” King said. “That’s actually a great thing for the survey research team because they get to learn something.”
Pollsters who’ve been proven wrong after the election — and that’s most of them — now have a great opportunity to improve their data collection and ultimately their forecasting prowess, King said.
Companies doing product or market research will have, he hopes, done the same: stumbled early on and then learned from their mistakes.
“There’s plenty of analytics where nobody learns anything; you just do it. And that’s not very good,” King said.
Rising use of mobile phones means pollsters have to rethink how to survey voters during elections. Read about it in this SearchCIO news story.
Marc Tanowitz, a fan of robotics process automation, would be the first to say the term has become a business buzzword.
“People plunk the word robotics in front of anything that is automated, because it sounds good,” he said in an interview with SearchCIO earlier this year. Indeed, the robotics process automation label has been slapped on technologies ranging from the industrial robots found on factory floors to an app that alerts you when an item on Amazon goes on sale.
As managing director at the IT advisory firm Pace Harmon, however, Tanowitz has made it his business to separate the RPA buzz from the benefits of this new technology. And, having advised clients on use cases for robotics process automation (aka RPA) for the past two years, he has some advice for CIOs: Get on it, already — or be prepared for another tussle over shadow IT.
“What is happening in the enterprise is that it is not IT that is driving automation; it is the business functions,” he said. “Not unlike what we saw with the business functions investigating SaaS and cloud platforms without the knowledge of the CIO, we see the same thing happening with robotics process automation.” Tanowitz advised CIOs to look at RPA as another enterprise collaboration tool that can help the business functions operate more efficiently.
Four tips for deploying robotic process automation
Robotics process automation is software that replicates how humans interact with the user interface of computers. The tools are lightweight, requiring minimal coding and little of the heavy lifting associated with other types of business software used for automating enterprise work — ERP implementations, for example, or business process management (BPM) suites.
Much like cloud was a few years ago, the applications are touted as business friendly but, like enterprise cloud applications and deployments, RPA projects need CIO oversight.
Here are four pointers from the Pace Harmon team to keep in mind as you embark on RPA. Go here for a link to the full article.
- Robotics process automation is not a replacement for traditional IT projects: RPA can be a good solution for automating a manual activity that is rules drive, data intensive, repetitive in nature and crosses multiple systems and decision points.
- Business and IT must collaborate for robotics process automation to succeed: Process owners often underestimate the need for IT involvement in RPA deployments, resulting in data security risks, latency issues and redundancy with other IT apps. IT and the business should develop a two-to-three year road map for RPA implementations to avoid these problems.
- Robotics process automation benefits go beyond direct cost savings: RPA also mitigates risk of human error, improves quality and frees up employees to focus on higher value work, thus improving job satisfaction and the reducing employee attrition.
- Robotics process automation will have an impact on outsourcing strategies: The immediate focus of RPA is to automate high volume, repeatable tasks. Next-generation RPA incorporates machine learning and natural language processing technology that will be used to automate more complex tasks. Outsourcing strategies that have relied on labor arbitrage to deliver business process savings need revising in light of the benefits offered by RPA.
One of the key attributes Curt Carver, vice president and CIO at the University of Alabama at Birmingham, looks for in a candidate is emotional maturity. But for some leaders, determining which candidates have the soft skill — and which don’t — can be illusive.
Carver, who served as an officer in the U.S. Army for more than 25 years, uses a couple of litmus tests to make the determination. The key behind both tactics? “I try to create opportunities for authentic and genuine conversations with the shields down to make sure they’re a good fit for the organization,” he said.
Get out of the office
Carver doesn’t perform interviews around a big table. Instead, he takes advantage of the university setting and invites the prospective hire on a walk around campus. The stroll creates a more casual setting, with Carver giving a tour along the way.
“It tends to lower their guard and you get a better sense of who the person is as we walk and talk about various topics around campus,” he said.
The answer to this question is telling
Carver uses this question at the end of every interview: What was the question you thought I was going to ask that I didn’t ask and what would be your answer to that question. “It throws people off, and the genuine person tends to come through,” he said.
The responses can be surprising. Those with emotional maturity talk about how they built a successful team. They talk about a significant accomplishment and why they’re proud of it — but eventually they turn back to a team endeavor or a moment when they empowered someone else or shattered a glass ceiling. “Those are examples, I think, of folks demonstrating empathy, demonstrating emotional maturity, talking about a difficult scenario or situation and how they handled it,” he said. “I think all of these are the right types of answers.”
Not all candidates respond that way. Some freeze up and don’t know how to answer the question; some don’t even attempt to answer the question, replying, instead that Carver covered everything. “That’s obviously not a good answer in an interview,” he said.
And others will take the opportunity to let their pride and hubris take over. One candidate responded by saying he thought he’d be asked about how great he is and then went on to talk how great he is. “I mean, seriously, that’s been an answer to the question,” he said.
Curt Carver promised to the staff, faculty and students that he would improve their lives in at least 100 ways during his first year as vice president and CIO at the University of Alabama at Birmingham. It’s an ambitious goal he achieved, and this year he plans to do it again.
The list of technology wins isn’t something he puts together. For that, he turns to the people whose lives he promised to make better. One of the ways he collects ideas is through a crowdsourcing site called the SPARK initiative. There, the community can suggest ideas for what’s needed or vote ideas already suggested up or down.
“The best decisions come by getting the community involved, creating a voice for everyone, creating the healthy exchange of ideas so that the best ideas through a meritocracy rise to the top,” he said. “The ideas that have the greatest impact on the community are the ones that we act on first.”
The list includes everything from stronger passwords to a faster network for research. “We’re doing all of this genomics research, and, yet, our high-performance computer was being funded out of IT reserves, which means it was not being funded,” he said. “A year later, we’ve got the fastest high-performance computer in the state. There was a 10- or 11-fold increase, depending on whether you’re looking at computer power or storage power.”
Engagement with the community is a key component for the 100 tech wins in a year. The crowdsourcing site is one avenue, but another is a monthly newsletter, which recipients can opt out of if they choose. There, he keeps the community up to date on the newest wins. “We want to be transparent about the things we’re working on and how they align back to the institution’s strategic plan and our strategic plan,” he said.
The enthusiasm has been infectious. Carver said it has helped connect his IT staff to the greater university, giving them an ability to see how what they do affects how the community functions. And his ideas — the newsletter, the crowdsourcing site — have been replicated by other departments at the university. “Imitation is the highest form of flattery,” he said.
Perhaps most stunning to Carver is the reception he’s had from his colleagues. At the end of his first year on the job, he experienced “something that’s never occurred in my life,” he said. What he thought was a budget meeting with his staff turned out to be a celebration of the 100 wins. “I walked into the room, and there were 300 people with cake and a celebration going on,” he said.