Blog

What’s New In Gartner’s Hype Cycle For CRM, 2019

By on October 19, 2019

  • Worldwide enterprise application software revenue totaled more than $193.6B in 2018, a 12.5% increase from 2017. CRM made up nearly 25% of the entire enterprise software revenue market.
  • 72.9% of CRM spending was on software as a service (SaaS) in 2018, which is expected to grow to 75% of total CRM software spending in 2019.
  • Worldwide spending on customer experience and relationship management (CRM) software grew 15.6%, from $41.7B in 2017 to $48.2B in 2018, and is projected to reach $55.2B in 2019.
  • Salesforce dominated the worldwide CRM market with a 19.5% market share in 2018, over double its nearest rival, SAP, at 8.3% share, according to Gartner’s market share estimates.
  • CRM revenue in 2018 is comprised of software and services revenue from Customer Service and Support (35.7%), Sales (25.9%), Marketing (25.4%), and Digital Commerce (13%). These four categories together comprise the customer experience and relationship management market, according to Gartner.

New technologies are proliferating across the CRM landscape, driven by the need every business has to understand, communicate, serve, and strengthen customer relationships. Gartner’s decision to create its first-ever Hype Cycle for CRM Sales Technology, 2019, reflects the widening spectrum of new technologies being introduced to improve sales effectiveness while improving operational efficiency. Gartner’s Hype Cycle for CRM Sales Technology, 2019 is based on an update to their Hype Cycle for CRM Sales, 2018.  Gartner’s definition of Hype Cycles includes five phases of a technology’s lifecycle and is explained here.  The Gartner Hype Cycle for CRM, 2019, is shown below:

Details Of What’s New In Gartner’s Hype Cycle For CRM, 2019

  • Four new technologies are on the Hype Cycle for CRM, reflecting enterprises’ need for greater integration of diverse systems and the demand for more predictive and prescriptive analytics-based insights. The four technologies include the following:
    • Blockchain for lead generation. Gartner sees the potential for blockchain to provide a decentralized peer-to-peer network model that supports exchanging data to the highest bidders using smart contracts. Gartner predicts this approach reduces or in some cases eliminates the need for a centralized authority such as a data intelligence solution. It also allows for a new ecosystem of managing, sharing and monetizing data for revenue-generating purposes.
    • Knowledge graphs for sales. The ability to build an AI-enabled knowledge model of real-world entities and their relationships to one another, expressed in a data schema, shows potential to increase sales effectiveness. Gartner predicts this emerging technology provides organizations with the ability to create data-driven sales organizations using graphs arranged in a network of nodes rather than in tables of rows and columns. The significance is the ability to correlate sales activities and benchmark against performance metrics in a more digestible and insightful way, which is often too complex for human analysis.
    • Digital adoption solutions. Gartner sees potential in this technology to improve the adoption of multiple tools across a selling and marketing organization. Digital adoption solutions enable sellers to onboard more quickly and improve productivity.
    • Relationship intelligence. By relying on machine learning, sales organizations can map out their universe of network connections, both internal and external, to identify potential avenues of engagement with any prospect or client. Gartner sees this as useful in its ability to provide warm introductions or even referrals for revenue-generating activities while reducing sales cycles.
  • Gartner predicts the following five technologies will deliver the most significant transformational benefits to selling organizations in 2 years or less. The five most transformation technologies in the near term are the following according to Gartner:
    • CPQ Application Suites
    • Digital Content Management for Sales
    • Lead Management
    • Partner Relationship Management (PRM)
    • Price Optimization and Management for B2B
  • The following CRM technologies have gained wide usage and adoption in the last year, as reflected by their position on this year’s Hype Cycle. Data intelligence solutions for sales, CPQ application suites, digital content management for sales, and sales KPI analytics are among the most adopted mature technologies on the hype cycle today.
  • Visual configurators have moved at a much faster pace to mainstream adoption along the Hype Cycle this year. Gartner credits visual configurators’ rapid adoption rate to how the majority of them are now embedded or easily integrated with configure, price, quote (CPQ) applications, or in digital commerce sites. State-of-the-art visual configurator is enabling engineering, production, and sales to become real-time collaborators in creating new products. For additional insights into visual configurators, please see How To Make Complex CPQ Selling Simple With Visual Configurators published earlier this week.
  • Algorithmic guided selling is now listed as obsolete. Gartner has re-assigned this technology as it’s now an embedded core capability in many CPQ and sales force automation (SFA) applications. By doing this, Gartner is saying it is doubtful algorithmic guided selling applications will be sold stand-alone in the future.
  • Social for sales and predictive B2B marketing analytics are off the CRM Hype Cycle. Gartner has chosen to merge them into the data intelligence solutions for the sales market. Social for sales is more of a process, not a technology market. The majority of social for sales-based strategies are executed over social networks that have the audience and scale to make them succeed, with LinkedIn being an example. Gartner believes the predictive B2B marketing analytics vendor landscape has shrunk and is not a viable market long term, as they have seen inquiries regarding market share in this area steadily drop in this area since 2016.
  • Gartner is seeing two main drivers of investment and innovation in CRM in 2019 and beyond. The first is digital optimization or a process and program of using digital technology to maximize existing operating processes and business models. The second is predictive/prescriptive-enabled technology or technology using capabilities such as machine learning that provides predictive signals and prescriptive “next best action” recommendations. Please see their research note, 4 Key Insights from the Gartner Hype Cycle for CRM Sales Technology, 2019, for additional details.

Sources:

4 Key Insights From the Gartner Hype Cycle for CRM Sales Technology, 2019, published October 2, 2019

Hype Cycle for CRM Sales Technology 2019, July 10, 2019 (Client access required)

Posted in , , , | Tagged , , , , , , , , , , | Leave a response

I’ve Got a Crazy Idea:  How About We Focus on Next-Quarter’s Pipeline?

By on October 18, 2019

I’m frankly shocked by how many startups treat pipeline as a monolith.

Sample CMO:  “we’re in great shape because we have a total pipeline of $32M covering a forward-four-quarter (F4Q) sales target of $10M, so 3.2x coverage.  Next slide, please.”

Regardless of your view on the appropriate magic pipeline coverage number (e.g., 2x, 3x, 4x), I’ve got a slew of serious problems with this.  What do I think when someone says this?

“Wait, hang on.  How is that pipeline distributed by quarter?  By stage?  By forecast category?  By salesrep?  You can’t just look at it as a giant lump and declare that you’re in great shape because you have 3x the F4Q coverage.  That’s lazy thinking.  And, by the way, you probably don’t even need 3x  the F4Q target, but you sure as hell need 3x this quarter’s coverage [1] and better be building to start next quarter with 3x as well.  You do understand that sales can starve to death and we can go out of business – the whole time with 3x pipeline coverage — if it’s all pipeline that’s 3 and 4 quarters, out?”

I’ve got a crazy idea.  How about as a first step, we stop looking at annual pipeline [2] and start looking at this-quarter pipeline and, most importantly, next-quarter pipeline?

What I’m told when I say this:  “No, no, Dave.  We can’t do that.  That’s myopic.  You need to look further out.  You can’t drive looking at the hood ornament.  Plus, with a 90-day average sales cycle (ASC) there’s nothing we can do anyway about the short term.  You need to think big picture.”

I then imagine the CMO talking to the head of demandgen:  “Yep, it’s week 1 and we only have 2.1x pipeline coverage.  But with a 90-day sales cycle, there’s nothing we can do.  Looks like we’re going to hit the iceberg.  At least we made our 3x coverage OKR on a rolling basis.  Hey, let’s go grab a flat white.”

I loathe this attitude for several reasons:

  • It’s parochial. The purpose of marketing OKRs is to enable sales to hit sales OKRs.  Who cares if marketing hit its pipeline OKR but sales is nevertheless flying off a cliff?  Marketing just had a poorly chosen OKR.
  • It’s defeatist. If “when the going gets tough, the tough get a flat white” is your motto, you shouldn’t work in startup marketing.
  • It’s wrong. The A in ASC stands for average.  Your average sales cycle.  It’s not your minimum sales cycle.  If your average sales cycle is 90 days [3] then you have lots of deals that close faster than 90 days, so instead of getting a flat white marketing should be focused on finding a bunch of those, pronto [4].

Here’s my crazy idea.  Never look at rolling F4Q pipeline again.  It doesn’t matter.  What you really need to do is start every quarter with 3.0x [5] pipeline.  After all, if you started every quarter with 3.0x pipeline coverage wouldn’t that mean you are teed up for success every quarter?  Instead of focusing on the long-term and hoping the short-term works out, let’s continually focus on the short-term and know the long-term will work out.

This brings to mind Kellogg’s fourth law of startups:  you have to survive short-term in order to exist long-term.

This-Quarter Pipeline
This process starts by looking at the this-quarter (aka, current-quarter) pipeline.  While it’s true that in many companies marketing will have a limited ability to impact the current-quarter pipeline — especially once you’re 5-6 weeks in — you should nevertheless always be looking at current-quarter pipeline and current-quarter pipeline coverage calculated on a to-go basis.  You don’t need 3x the plan number every single week; you need 3x coverage of the to-go number to get to plan.  To-go pipeline coverage provides an indicator of confidence in your forecast (think “just how lucky to do we have to get”) and over time the ratio can be used as an alternative forecasting mechanism [6].

this qtr togo

In the above example, we can see a few interesting patterns.

  • We start the quarter with high coverage, but it quickly becomes clear that’s because the pipeline has not yet been cleaned up. Because salespeople are usually “animals that think in 90-day increments” [7], next quarter is effectively eternity from the point of view of most salesreps, so they tend to dump troubled deals in next-quarter [8] regardless of whether they actually have a next-quarter natural close date.
  • Between weeks 1 and 3, we see $2,250K of current-quarter pipeline vaporize as part of sales’ cleanup. Note that $250K was closed – the best way for dollars to exit the pipeline!  I always do my snapshot pipeline analytics in week 3 to provide enough time for sales to clean up before trying to analyze the data.  (And if it’s not clean by week 3, then you have a different conversation with sales [9].)
  • Going forward, we burn off more pipeline to fall into the 2.6 to 2.8 coverage range but from weeks 5 to 9 we are generally closing and burning off pipeline [10] at the same rate – hence the coverage ratio is running in a stable, if somewhat tight, range.

Next-Quarter Pipeline
Let’s now look at next-quarter pipeline.  While I think sales needs to be focused on this-quarter pipeline and closing it, marketing needs to be primarily focused on next-quarter pipeline and generating it.  Let’s look at an example:

next qtr pipe

Now we can see that next-quarter plan is $3,250K and we start this quarter with $3,500K in next-quarter pipeline or 1.1x coverage.  The 1.1x is nominally scary but do recall we have 12 weeks to generate more next-quarter pipeline before we want to start next quarter with 3x coverage, or a total pipeline of $9,750K.  Once you start tracking this way and build some history, you’ll know what your company’s requirements are.  In my experience, 1.5x next-quarter coverage in week 3 is tight but works [11].

The primary point here is that given:

  • Your knowledge of history and your pipeline coverage requirements
  • Your marketing plans for the current quarter
  • The trends you’re seeing in the data
  • Normal spillover patterns

That marketing should be able to forecast next quarter’s starting pipeline coverage.  So, pipeline coverage isn’t just an iceberg that marketing thinks we’ll hit or miss.  It’s something can marketing can forecast.  And if you can forecast it, then you adjust your plans accordingly to do something about it.

Let’s stick with our example and make a forecast for next-quarter starting pipeline [12]

  • Note that we are generating about $250K of net next-quarter pipeline per week from weeks 4 to 9.
  • Assume that we are continuing at steady-state the programs generating that pipeline and ergo we can assume that over the next four weeks we’ll generate another $1M.
  • Assume we are doing a big webinar that we think will generate another $750K in next-quarter pipeline.
  • Assume that 35% of the surplus this-quarter pipeline slips to next-quarter [13]

If you do this in a spreadsheet, you get the following.  Note that in this example we are forecasting a shortfall of $93K in starting next-quarter pipeline coverage.  Were we forecasting a significant gap, we might divert marketing money into demand generation in order to close the gap.

fc next qtr

All-Quarters Pipeline
Finally, let’s close with how I think about all-quarters pipeline.

all qtr

While I don’t think it’s the primary pipeline metric, I do think it’s worth tracking for several reasons:

  • So you can see if pipeline is evaporating or sloshing. When a $1M forecast deal is lost, it comes out of both current-quarter and all-quarters pipeline.  When it slips, however, current-quarter goes down by $1M but all-quarters stays the same.  By looking at current-quarter, next-quarter, and all-quarters at the same time in a compact space you can get sense for what is happening overall to your pipeline.  There’s nowhere to hide when you’re looking at all-quarters pipeline.
  • So you can get a sense for the size of opportunities in your pipeline.  Note that if you create opportunities with a placeholder value then there’s not much  purpose in doing this (which is just one reason why I don’t recommend creating opportunities with a placeholder value) [14].
  • So you can get a sense of your salesreps’ capacity. The very first number I look at when a company is missing its numbers is opportunities/rep.  In my experience, a typical rep can handle 8-12 current-quarter and 15-20 all-quarters opportunities [15].  If your reps are carrying only 5 opportunities each, I don’t know how they can make their numbers.  If they’re carrying 50, I think either your definition of opportunity is wrong or you need to transfer some budget from marketing to sales and hire more reps.

The spreadsheet I used in this post is available for download here.

# # #

Notes

[1] Assuming you’re in the first few weeks of the quarter, for now.

[2] Which is usually done using forward four quarters.

[3] And ASC follows a normal distribution.

[4] Typically, they are smaller deals, or deals at smaller companies, or upsells to existing customers.  But they’re out there.

[5] Or, whatever your favorite coverage ratio is.  Debating that is not the point of this post.

[6] Once you build up some history you can use coverage ratios to predict sales as a way of triangulating on the forecast.

[7] As a former board member always told me — a quote that rivals “think of salespeople as single-celled organisms driven by their comp plan” in terms of pith.

[8] Or sometimes, fourth-quarter which is another popular pipeline dumping ground.  (As is first-quarter next year for the truly crafty.)

[9] That is, one about how they are going to get their shit together and manage the pipeline better, the first piece of which is getting it clean by week 3, often best accomplished by one or more pipeline scrub meetings in weeks 1 and 2.

[10] Burning off takes one of three forms:  closed/won, lost or no-decision, or slipping to a subsequent quarter.  It’s only really “burned off” from the perspective of the current-quarter in the last case.

[11] This depends massively on your specific business (and sales cycle length) so you really need to build up your own history.

[12] Technically speaking, I’m making a forecast for day-1 pipeline, not week-3 pipeline.  Once you get this down you can use any patterns you want to correct it for week 3, if desired.  In reality, I’d rather uplift from week 3 to get day-1 so I can keep marketing focused on generating pipeline for day-1, even though I know a lot will be burned off before I snapshot my analytics in week 3.

[13] Surplus in the sense that it’s leftover after we use what we need to get to plan.  Such surplus pipeline goes three places:  lost/no-decision, next-quarter, or some future quarter.  I often assume 1/3rd  goes to each as a rule of thumb.

[14] As a matter of principle I don’t think an opportunity should have a value associated with it until a salesrep has socialized a price point with the customer.  (Think:  “you do know it cost about $150K per year to subscribe to this software, right?”)  Perversely, some folks create opportunities in stage 1 with a placeholder value only to later exclude stage 1 opportunities in all pipeline analytics. Doing so gets the same result analytically but is an inferior sales process in my opinion.

[15] Once you’re looking at opportunities/rep, you need to not stop with the average but make a histogram.  An 80-opportunity world where 10 reps have 8 opportunities each is a very different world from one where 2 reps have 30 opportunities each and the other 8 have an average of 2.5.

(Cross-posted @ Kellblog)

Posted in , , | Tagged , , , , , | Leave a response

Scaling Cloud Services Is Key To Growing A Digital Business

By on October 16, 2019

Scaling Cloud Services Is Key To Growing A Digital Business

  • 93% of enterprises are securing remote locations with a centralized approach that rarely scales to secure every endpoint and identity of remote branch locations, leaving an enterprise more vulnerable to a breach.
  • Enabling network security is the greatest challenge enterprises face when managing a highly distributed network with numerous remote locations.
  • In an era of cloud-first networks, 9 out of 10 companies are still relying on centrally managed networks that don’t scale for remote system users, creating productivity bottlenecks.
  • 75% of enterprises experience branch and remote location network interruptions several times a year or more frequently, costing an organization thousands of dollars an hour in lost productivity.

The challenges of scaling cloud services to grow a digital business are many and are well-explained in the recent research report, Remote Office Networks Pose Business and Reliability Risk A Survey of IT Professionals (27 pp., PDF, no opt-in), published on August 2019 by Dimensional Research in collaboration with Infoblox. This report provides valuable insights into why scaling cloud services is essential for growing a digital business. The study’s findings reflect how remote branch and production locations’ lack of IT security and site personnel are one of the most challenging constraints to overcome and keep growing their business. Please see page 22 of the study for specifics on the methodology.

99% or nearly all enterprises with distributed operations suffer adverse business impacts from network interruptions. Of the many causes of network disruption, one of the most common is not directing traffic to the closest point of entry into cloud platforms. Taking a software-based approach to wide-area networking (SDWAN) is proving effective in improving cloud-based application performance, including Microsoft Office 365 cloud-based application performance. The report shows how SD-WAN is replacing outdated centralized IT models that lack the scale to flex and support new digital business models.

Key insights from the research report include the following:

  • Enterprises realize the model of relying on centralized IT security isn’t scaling to support and protect the proliferation of user devices with internet access, leaving branch offices less secure than ever before. Every IT architect, IT Director, or CIO needs to consider how taking an SDWAN-based approach to network management reduces the risk of a breach and data exfiltration. 93% of enterprises are securing remote locations with a centralized approach that rarely scales to secure every endpoint and identity of remote branch locations, leaving an enterprise more vulnerable to a breach. Enterprises are upgrading their core network services, including DNS, DHCP, and IP address management, on cloud-based DDI platforms to bring greater security scale and reliability across their enterprise networks. Enterprises are also devising Zero Trust Security (ZTS) frameworks to secure every network, cloud, and on-premise platform, operating system, and application across their branch offices. Chase Cunningham of Forrester, Principal Analyst, is the leading authority on Zero Trust Security, and his recent video, Zero Trust in Action, is worth watching to learn more about how enterprises can secure their IT infrastructures. You can find his blog here.

  • 75% or the majority of an enterprises’ branch offices experience network interruptions several times a year, with 49% of them requiring three or more hours to resolve remote office network outages. Enterprises continue to pay a very high price in lost productivity due to network interruptions and the time it takes to troubleshoot them and get a branch or remote location back online. Enterprises are upgrading their core network services, including DNS, DHCP, and IP address management, on cloud-based DDI platforms to bring greater scale and reliability across their enterprise networks. Cloud-based DDI platforms enable enterprises to manage networking for hundreds to thousands of remote sites with unprecedented cost-efficiency.

  • Relying on centralized IT creates many challenges and security threats for remote offices, with the most costly not having IT staff at remote sites. Network security at remote locations is the greatest challenge enterprises face when managing a highly distributed network with numerous remote locations. A contributing factor to security being the leading challenge of managing a highly distributed network is the lack of IT employees at remote branches. 65% of enterprises are routinely sending IT employees to remote branches to resolve networking issues alone. Travel costs combined with lost productivity from having to send IT technicians out for a week or longer to solve network performance issues is another reason why enterprises are adopting cloud-based DDI platforms.

  • Enterprises are adopting cloud-based DDI platforms that enable enterprises to simplify the management of highly distributed remote networks as well as to optimize the network performance of cloud-based applications. Dimensional Research’s study reflects how enterprises are meeting the challenge of increasingly complex, distributed networks that have a proliferating number of remote locations and endpoints. The majority of enterprises, 71%, are looking to integrate core network services, DNS, DHCP, and IP address management, into a single cloud-based DDI platform. The problem is, conventional DDI solutions for branch locations are too slow or complicated for a cloud-first world. The following graphic from the study shows what motivating enterprises to adopt SD-WAN today is.

Posted in , , , | Tagged , , , , , | Leave a response

How To Make Complex CPQ Selling Simple With Visual Configurators

By on October 14, 2019

Bottom Line: Realizing visual configurators’ full potential starts by enabling engineering, production, and sales to become real-time collaborators in creating new products.

2D, 3D, Augmented Reality (AR), Mixed Reality (MR), and Virtual Reality (VR) visual configurators are proliferating across the Configure, Price, and Quote (CPQ) landscape today. Manufacturing marketing teams say they are the most effective lead generation technology they have, responsible for 40%+ growth in Marketing Qualified Leads (MQLs) this year alone. Sales VPs and Chief Revenue Officers (CROs) are seeing from 9% to 30% improvements in deal close rates and over 90% increases in quote accuracy. Visual configurators deliver shock-and-awe to prospects and drive more leads and deals.

Product Models Need To Scale, Driving Greater Collaboration

The good test of any product configurator is whether it can scale from assemble-to-order (ATO) to Engineer-To-Order (ETO) while enabling real-time collaboration between engineering, production, and sales. A given products’ many attributes and options defined by engineering in their PLM system need to be consistent with manufacturing’s work instructions and Bill of Materials (BOM) in their ERP system. And the visual configurator sales & marketing is using needs to reflect, in real-time, what engineering defined in PLM and what manufacturing’s ERP system can build. Product models serve as the master data that enables real-time collaboration between engineering, manufacturing, and sales.

Visual configurators need to push beyond the veneer of delivering shock-and-awe and enable real-time collaboration between PLM, ERP, and CRM & CPQ systems to achieve their full potential. Visual configuration providers need to pursue the goal of enabling engineering, manufacturing, and sales to be collaborators in creating accurate products and challenge themselves to deliver the following:

  • Improve sales performance while increasing margin per deal by providing only the options that are the most buildable at the lowest cost.
  • Eliminate disconnects between what engineering designed and what manufacturing can produce leads to more sales at higher gross margins.
  • Close product configuration gaps and improving fulfillment speed and product quality, creating greater customer loyalty and follow-on sales.
  • Automatically propagate product and design changes across all functional areas to accelerate new products to market while improving product quality.
  • Real-time fine-tuning of new product features to the model level that specific customers want becomes possible when engineering, manufacturing, and sales are collaborating in real-time.
  • Update work instructions and BOMs in real-time based on changes customers make in product visualizations.
  • Improve the balance of revenue across configurable products to sell higher-margin models based on real-time collaboration between PLM, ERP, CRM, and CPQ systems.
  • See in real-time how changes in product design, Bill of Materials (BOM), and delivery dates impact the financial performance of a manufacturer.

Predicting Visual Configuration’s Future

Shortening cycle times from product concept to completed product is the secret to succeeding with visual configuration. And when each manufacturing cycle time has its cadence or speed depending on how little or much a customer wants a product customized, visual configurators need to flex and deliver what customers want when.

Companies defining the future of visual configuration today include CDS, DERWID, and SAP Visual Enterprise. These three companies are defining the future of visual configuration by enabling real-time integration between PLM, ERP, CRM, and CPQ systems.  I recently spoke with John Major, CEO of CDS to get his insights into what’s driving visual configuration’s success today.  “What we’re seeing in the marketplace now are two things. One is the clients want to understand how our visual configuration solution is going to fit into their change management as it’s rooted in PLM, because to any manufacturer, PLM reigns supreme,” he said. He continued, “The second is about staffing. When you’re a manufacturing company, and you buy a visual configurator toolkit that requires you to create your app, a few things happen. You need to staff up a software team to now run that toolkit and write development. So your long-term cost is fairly significant versus a company that can deliver an entire solution at scale.” 

CDS is partnering with eLogic, who is regarded as the leading system integration partner in CPQ and product configuration and is considered a global leader in delivering business solutions for manufacturers across SAP configuration technologies and Microsoft Dynamics 365, Power Platform & Azure. Together they are delivering next-generation visual configuration solutions for their shared clients. Examples of the work they are doing are shown below:

  • Real-time model updates keep engineering, manufacturing, and sales in sync. When customers are designing a new product in a CPQ session, the model is updated in real-time and saved, so engineering, manufacturing, and sales can see how their changes affect the product. An example of this is shown below:

  • When the product is configured “to scale,” 2D proposal drawings are automatically generated, and the product model is updated in real-time, making augmented reality visualizations possible. 3D models are also made available in a variety of CAD formats. Additionally, an Augmented Reality model is created that can be placed in any virtual environment. What’s noteworthy is that while the model’s appearance is changing, all relevant changes to the work instructions and BOM are happening in real-time using the SAP Visual Enterprise

  • When product models are the catalyst enabling real-time collaboration between engineering, manufacturing, and sales, selling into the aftermarket becomes profitable. Aftermarket selling has a complexity all its own. Taking on the challenge of shortening cycle times from product concept to completed products in the market is what’s needed today. The example below shows a piece of equipment selected in CPQ, then rotated, zoomed in, and exploded to see the internal components. Internal parts can now be selected, quoted, ordered and delivered for replacement.

Conclusion

Visual configurators are capable of so much more than they are delivering today. It’s time to graduate beyond the shock-and-awe stage, which has been very successful in driving leads, generating MQLs, and closing deals. It’s time to get down to the hard work of making all those impressive models buildable at scale and profitable. And that comes by doubling down efforts at shortening cycle times from product concept to completed product. That’s the true north of this market and the secret to succeeding. Getting engineering, manufacturing, and sales collaborating using product models as a single source of truth is the best place to start.

Posted in , , , | Tagged , , , , , , , | Leave a response

Breaking Down Silos in your Business

By on October 11, 2019

Every organisation in every sector is dealing with digital disruption in today’s volatile, fast changing and uncertain world.  Businesses need to transform to stay competitive or be in danger of going the way of once great brands like Nokia, Blockbuster or Kodak who saw the writing on the wall but didn’t act fast enough to adapt.  Too often digital transformation efforts fail with a regular cause being the organisation seeing the task as a project with a beginning and an end.  Those organisations leading in this era of disruption recognise that transformation needs to be continuous and businesses need to think of being in a permanent state of reinvention.  But often, the key barrier to change is the siloed nature of most organisations.  In today’s connected world, that needs to change, and we believe the way to solve the problem combines different thinking in terms of people, culture and architecture, as well as a new approach to systems integration, making use of the API Economy.

There is plenty of research exploring how business has evolved over the 19th and 20th centuries.  The various parts of a typical organisation often fail to work together with a shared sense of mission.   We would argue that the structural issue of divisions is a natural result of the command and control and hierarchical management approach of most, and particularly larger, organisations.  Most large companies have divisions, or even groups and functions within divisions, that operate in silos.  Even the word “division” itself highlights the problem.  People are, by their nature, territorial.  Those functional teams that grew with an objective of efficiency and process simplification in the beginning, have created issues around territory and mistrust that can derail the cross functional thinking and new ideas that are required in the 21st century of the Fourth Industrial Revolution.

In looking at the people and culture issues we are guided by Professor Vlatka Hlupic and the research behind her book The Management Shift.  She has investigated companies who have been tackling these big shifts over a number of years.  She references more than 20 companies using her approach and leadership model.  They are from small to large, in various sectors and include a FTSE 100 Company.  She has categorised their management styles in 5 stages or levels from Traditional to Emergent.  The traditional companies haven’t moved beyond command and control and silos.  The smart, successful companies have an emergent management style characterised by an unlimited mindset, strong team cohesion, unbounded culture, inspirational leaders, a strong sense of purpose, and a passion for the work.  These are the characteristics we need in our 21st century leaders and managers to break down barriers, encourage cross functional teams and foster the right mindset for collaboration rather than conflict.

We also think that the silo problem is a manifestation of Conway’s Law where organsations are constrained to design systems which are copies of the communication structures of that organisation.  We need to be thinking, communicating and doing things differently.

Given the ubiquity of IT in the way enterprises are organising their business, one cannot tackle breaking down silos in an organisation without addressing it at a technology level as well as people level.  Data silos are  the result of cultural, organisational and technical choices that were made long ago, either for strategic reasons or because of technical limitations. They reduce productivity, they make it difficult to have a global view of your business, and they make it difficult to leverage the new technology available today.

Over the past 10 years, the start-ups who managed to create new business models managed to do it because they leveraged the new technology available to them and did not have the legacy to deal with.  They could build everything from the ground up, at a speed unheard of before.  15 years ago, no organisation would have had the resources to develop geo-localisation, mobile apps, mobile payment, booking system, and scale as Uber did in such a short amount of time.  Equally they had no organisational barriers to deal with. They were purpose built and organised from the ground up. They had an idea and leveraged the cloud to pick and choose what functionality they needed to make this idea reality.

In order to stay current, to re-invent themselves and stay relevant to their ever more demanding clients, enterprises need to be agile and break down the silos that they built over the years. To achieve this, they need to be able to develop applications extremely rapidly, matching what the business needs, and ready to iterate to deliver fast.  However today, it is still considered that 50% of these projects fail because of integration issues.

Historically, integration teams have always been very centralised, being themselves one of the silos they should be contributing to break with integration technology. We are used to refer to the SOA team, or the ESB team. Integration was not something a developer would do on an ad-hoc basis, it was a full-time job, needing deep expertise in integration tools. This became very acute when the service-oriented architecture was put in place. It forced the creation of a centralised team to create the service layer that had to be used by the developers to developer their applications. The problem is that the integration team did not understand the application their services were created for and it created friction and finally slowed down the pace of developing new applications. It was clear that the best approach would have been to let the application team own the creation of the integration services, but technology did not allow that.

Over the past few years, new techniques have allowed us to re-think the way we tackle integration.  Let’s take a quick look at some new concepts and how they help moving towards a decentralized integration team.

Fine Grained Integration & Microservices

Breaking up your enterprise wide deployed integration hub into right sized containers provides improved agility, scalability, and resilience.  Agility, because many teams can work on integrations without having to defer to a centralised integration team. Scalability, because individual flows can be scaled on their own.  Resilience, because isolated flows cannot steal shared resources such as CPU from one to another.

Microservices are a software development technique that allows you to decompose an application into smaller de-coupled services. They provide greater agility because they can be changed independently from one to another, they are scalable because we can tie their usage with the resources they need, and they provide better overall application resilience because they are independent from one to another.

As we have seen, fine grained integration architecture and Microservices are providing similar advantages, and once brought together they bring the developers the environment they need to be fast, to be independent and to be able to concentrate on their part of the application.

APIs

API solutions have come a long way and today provide the tooling to be offered and consumed easily. They provide tools to be easily discoverable, they allow the provider to secure them and control the on-boarding of users.  They provide analytics so you can monitor them and control their usage, they can be promoted to third parties and they now can also be monetised.  The API economy is here, and the companies adopting the approach are more successful – research shows it adds more than 10% to the firm’s market value.

APIs therefore provide a very simple way for the provider to “offer” access to its data, and to the consumer to get to the service he or she needs. Based on a modern integration architecture, they are the key to unlock the data new technologies need to deliver on their premise. AI is only as good as the data it can be trained on. Innovative mobile application are only worth it if they allow the end user accessing and manipulating meaningful data.

The combination of Microservices consuming APIs to get to integration points can give an organisation great prospects in terms to speed and agility to respond to changing business needs.

People

We have seen that technology can change the way integration teams are organised, and give more autonomy to application developers.  But technology should also provide non-technical teams access to data. Take the example of the HR department that decided to subscribe to a Workday SaaS service. It is likely they did this without involving IT much – remember shadow IT – (at least during the choice of the solution). They did this because they wanted access to that application simply, without having to wait for a long IT development cycle, and were ready to adapt to get to the functionality. Now the HR department is using Workday and they need to access some specific information and want to receive an email alert when there is a specific change. For them, for simple integration requests like this, reverting to asking IT is out of the question. Modern integration tools should have “ready to use” connectors allowing them to perform no-code integration tasks.

Of course, technology used to create the silos we are trying to break. Over specialisation created barriers between the business and IT.  Within IT, it created barriers between integration specialists and developers, and it certainly didn’t facilitate communication between an enterprise and the “outside” world. Today, the need for data to fuel new technologies such as AI, Blockchain and other emerging technologies forces us to break down these barriers. And that’s what new technology and techniques allow us to do. It gives greater autonomy to the developer, it allows business users to be self-sufficient for their simpler needs, with a new level of controlled self-service thanks to APIs and the API Economy.

In summary, for today’s organisation to stay ahead of the competition it needs both a new mindset and a new approach to technology addressing architecture, technology and people. It needs more open leadership that recognises cross functional teams are necessary and better teamwork is required at all levels.  It needs a more agile approach to management as well as technology.  In terms of the technology deployed to support transformation, it needs to recognise that integration is the key driver, and the creation of APIs to open up company data reduces friction, drives new business models and creates new revenue opportunities.

Contact us if you want to find out more about making integration and APIs work for your business.

This post is a collaboration co-authored by Emmanuel Treny, Director Sales Europe – IBM Cloud Integration and David Terrar, Founder & CXO of Agile Elephant.

(Cross-posted @ Agile Elephant)

Posted in , | Tagged , , , , , , , , , | Leave a response

TAMyopia

By on October 11, 2019

When I was at PwC in the early 90s, I remember we used to throw out statements like “we have 40 to 50% market share in the SAP (or PeopleSoft) implementation market” When I got to Gartner I saw their competitors were saying similar stuff. So, I started telling them – “no, actually you have less than 10%” . The tune of at least some of them turned to “we have 50% market share of deals we choose to chase”. Choice – certainly their prerogative which segments or verticals they chose to focus on. But it’s not a reflection of Total Addressable Market.

One of my favorite advisory projects is helping vendors challenge their previous definitions of TAM.

I have seen plenty of dysfunctional behavior from technology vendors of every shape when their TAM definition is narrow  – salespeople chasing deals convenient to them, not what the leadership would have approved, marketing claims to deliver functionality in areas which their R&D had no intention of developing in any meaningful manner, CFOs and investment committees which don’t approve enough R&D and Capex needed to keep their entities competitive.

In my recent book, I outlined several trillion dollar markets that many technology vendors have missed since the late 90s. Those included smart products, digital marketing, IoT, cloud infrastructure, various verticals – – Google, Facebook, Amazon, Foxconn, GE, Siemens and a whole bunch of vertical players have thrived in those markets even as many technology vendors ignored them. Download the chapter from my recent book  in link here if you want to read about all the missed markets.

Many of those markets were brand new ones or what in MBA school we called adjacent markets so you can understand why so many vendors ignored them – even as they now wish they had entered those markets. But even in their core focus markets, I have seen many a myopic definition of TAM. Here are a few examples

a) Automation and Outsourcing

When I wrote Silicon Collar three years ago, I chose the title because it felt like traditional definitions of white, blue, pink collars were dated as technology was reshaping every job, everywhere. We all wear a Silicon collar these days.  I had examples of robotics, drones, machine learning, CGI, exoskeletons, robotic process automation (RPA) and other automation in the oil patch, in accounting, in films, in winemaking, garbage collection and many other sectors. I wasn’t dreaming this up – executives at sophisticated companies were in the book describing their experiences.

So, it has been a bit disconcerting to see so many outsourcers have glommed onto RPA as their major (in many cases only) focus when it comes to automation. Even more cynically, most outsourcers do not take seriously repeated customer expectations to automate their own labor intensive services.

b) Data Centers and networks

I cannot believe how envious many vendors are of AWS’s and Azure’s recent success. On the other hand, I cringe when I hear software vendors and many outsourcers say “glad we didn’t have to invest billions in Capex”. The reality is less than a decade ago HP(with EDS), Oracle (with Sun), IBM, Accenture, Verizon, Deutsche Telecom and other telcos populated and ran data centers and networks for the world. The emerging cloud infrastructure market was theirs to lose and they have done so – spectacularly, so far.

Many SaaS vendors view the cloud infrastructure market as a bonanza – let someone invest the Capex, we will just rent it for cheap. It’s not really that cheap and increasingly they are being expected to support multiple clouds. Zoho has continued to invest in its own data centers and passing along those savings to customers. The time will come for other software vendors to similarly hedge their bets. They will have to expand, or at least, morph their market definition of infrastructure.

c) “Glo-ver” in SaaS

I have increasingly been pointing out a huge under-achievement in the enterprise applications market. After two decades of cloud and in-memory applications, only about 20% of a grid across countries and industry processes has a decent choice in contemporary architecture. Myths persist such as “verticals are a sink hole”. Sure if you dont do it right, but go see how much lock-in revenue and margins SAP has enjoyed with its vertical investments in the early 2000s.

I have accelerated my coverage of applications and executives who are focused on the white spaces – see some of that coverage summarized here in a trend I call Glo-ver  expansion in focus.

Back to helping vendors challenge their previous definitions of TAM.  Those are fun projects when the vendor is willing to open up. I must be honest though – many vendors look to influence analysts, not use them much for intelligence. So, they would rather posture they have “50% market share in deals they choose to chase”.

Seriously, I hope that changes. Too many vendors are defining markets too narrowly and finding their competitors have done the same and a result too many are chasing after the same, narrow markets. That is a sure path to commoditization.  Trust me – I have seen it repeated many a times over the last three decades. There is little safety in those numbers.

 

(Cross-posted @ Deal Architect)

Posted in , | Tagged , , , , | Leave a response

How To Improve Your CPQ Pricing Strategies

By on October 11, 2019

Manufacturers can get more than their fair share of channel sales and margins by improving price management for every dealer, distributor, and reseller they sell-through. It’s possible to expand earnings by 50% on slight increases in volume when pricing is consistent channel-wide. McKinsey’s latest research on the topic, Pricing: Distributors’ Most Powerful Value-Creation Lever, shows how the highest performing distributors use pricing to create value. For manufacturers competing for more sales through distributors, they share with competitors, improving their channel partners’ margins is the single best strategy to win more sales and long-term loyalty.

  • A 1% price increase yields a 22% increase in Earnings before Interest & Taxes (EBITDA) margins for distribution-based businesses.
  • It would take a 7.5% reduction in fixed costs to achieve the same 22% increase in EBITDA that a 1% increase in pricing achieves.
  • A distribution-based business would need to increase volume by 5.9% while holding operating expenses flat to achieve the same impact as a 1% price increase.
  • Channel partners are more loyal to margin than manufacturers, which is why price management needs urgent attention on CPQ roadmaps.

CPQ Strategies Need To Deliver More Margin Back To The Channel

The typical manufacturer who has over $100M in sales generates 40% or more of their sales through indirect channels. The channel partners they recruit and sell through are also reselling 12 other competitive products on average. Which factors most influence a distributor or channel partner’s decision to steer a sale to one manufacturer versus another?  The following are the steps manufacturers can take now to improve price management and drive more channel sales:

  • Upgrade the pricing module in CPQ to deliver more than configurable price lists to include pricing waterfalls, automated approval levels for pricing requests, and discounts. Distributors drive more deals to manufacturers whose CPQ systems are designed to give them greater freedom in tailoring pricing to every customer and selling situation they have. Automating approval levels using machine learning-based supervised algorithms that serve as pricing guardrails on every quote a channel partner creates is proving effective at delivering a 1% price increase which drives margin back to resellers. The more a manufacturer can make margins flow back to its channel partners, the faster the channel partners can grow. The following graphic from McKinsey’s latest pricing research illustrates why.

  • Distributors will drive more deals to manufacturers who automate pricing approvals, guiding their sales teams to the largest and most profitable deals first. One of the best ways to compete and win more deals through channel partners is to achieve the ambitious goal of delivering pricing approval within seconds on a 24/7 basis. Pricing needs to provide guardrails that guide channel sales reps to the largest, most profitable, and most ready-to-buy new and aftermarket sales opportunities. Manufacturers capturing more channel sales are relying on machine learning-based pricing systems that optimize price approvals while recommending only those new and aftermarket deals that will drive a 1% or greater price increase. Machine learning is making solid contributions to automating pricing approvals. It’s proving most effective when it is balanced with the flexibility of responding to subjective competitive situations where pricing on specific products need discounts to win deals in aggregate. The following workflows from Deloitte explain how this is being accomplished today:

  • Helping distributors solve sales compensation problems by improving price management drives more deals in the short-term and keep distributors in business long-term. Distributors start out building their sales comp plans on volume and growth alone. The problem is comp plans reward revenue growth at the expense of profits. That’s making it harder every year for distributors to stay in business. Manufacturers delivering new pricing management and optimization apps in their CPQ platforms need to provide real-time guidance on margin potential by the deal, pricing waterfall logic that includes margins, contract pricing overrides for margins and more if they are going to help their distributors stay in business.

Conclusion – Pricing Is the Engine Powering CPQ’s Market Growth Today

Manufacturers who excel at growing indirect product and services revenue through channels realize that every one of their channel partners is more loyal to pricing and margins than any specific vendor they resell. Providing a CPQ application or platform they can personalize, and automate workflows is just the beginning. The bottom line is that manufacturers need to put more intensity into improving pricing today if they’re going to hold onto the distributors they have and attract new ones.

Pricing is the primary catalyst driving the CPQ market’s growth as well. According to Gartner, the CPQ grew 36% in 2017, reaching $1.084B with the majority of growth attributable to cloud-based solutions. It’s no wonder CPQ is considered one of the hottest CRM technologies for the foreseeable future, projected to grow at a 25% Compound Annual Growth Rate (CAGR) through 2020. Supervised machine learning algorithms capable of providing guardrails in real-time for every potential deal a reseller sales representative has is what’s needed to protect a distributor’s margins. Winning more deals with channel partners starts by respecting how vital margins are to their success and improving pricing management as part of a broader CPQ strategy that delivers results.

Sources:

Configure, Price, and Quote (CPQ) Capabilities: Why the right CPQ capability is key to transitioning to a flexible consumption model, 8 pp., PDF, no opt-in, Deloitte, 2019.

Pricing: Distributors’ Most Powerful Value-Creation Lever, McKinsey & Company, September 2019.

Posted in , , , | Tagged , , , , , , , | Leave a response

It’s Time To Solve K-12’s Cybersecurity Crisis

By on October 8, 2019

College study group brainstorming together in classroom or library

  • There were a record 160 publicly-disclosed security incidents in K-12 during the summer months of 2019, exceeding the total number of incidents reported in all of 2018 by 30%.
  • 47% of K-12 organizations are making cybersecurity their primary investment, yet 74% do not use encryption.
  • 93% of K-12 organizations rely on native client/patch management tools that have a 56% failure rate, with 9% of client/patch management failures never recovered.

These and many other fascinating insights are from Absolute’s new research report, Cybersecurity and Education: The State of the Digital District in 2020​, focused on the state of security, staff and student safety, and endpoint device health in K-12 organizations. The study’s findings reflect the crisis the education sector is facing as they grapple with high levels of risk exposure – driven in large part by complex IT environments and a digitally savvy student population – that have made them a prime target for cybercriminals and ransomware attackers. The methodology is based on data from 3.2M devices containing Absolute’s endpoint visibility and control platform, active in 1,200 K-12 organizations in North America (U.S. and Canada). Please see the full report for complete details on the methodology.

Here’ the backdrop:

  • K-12 cybersecurity incidents are skyrocketing, with over 700 reported since 2016 with 160 occurring during the summer of 2019 alone. Educational IT leaders face the challenge of securing increasingly complex IT environments while providing access to a digitally savvy student population capable of bypassing security controls. Schools are now the second-largest pool of ransomware victims, just behind local governments and followed by healthcare organizations. As of today, 49 school districts have been hit by ransomware attacks so far this year.

“Today’s educational IT leaders have been tasked with a remarkable feat: adopting and deploying modern learning platforms, while also ensuring student safety and privacy, and demonstrating ROI on security and technology investments,” said Christy Wyatt, CEO of Absolute.

Research from Absolute found:

K-12 IT leaders are now responsible for collectively managing more than 250 unique OS versions, and 93% are managing up to five versions of common applications. The following key insights from the study reflect how severe K-12’s cybersecurity crisis is today:

  • Digital technologies’ rapid proliferation across school districts has turned into a growth catalyst for K-12’s cybersecurity crisis. 94% of school districts have high-speed internet, and 82% provide students with school-funded devices through one-to-one and similar initiatives. Absolute found that funding for educational technology has increased by 62% in the last three years. The Digital Equity Act goes into effect this year, committing additional federal dollars to bring even more technology to the classroom. K-12 IT leaders face the daunting challenge of having to secure on average 11 device types, 258 unique operating systems versions and over 6,400 unique Chrome OS extensions and more, reflecting the broad scale of today’s K-12 cybersecurity crisis. Google Chromebooks dominate the K-12 device landscape. The following graphic illustrates how rapidly digital technologies are proliferating in K-12 organizations:

  • 42% of K-12 organizations have staff and students regularly bypass security endpoint controls using web proxies and rogue VPN apps, inadvertently creating gateways for malicious outsiders to breach their schools’ networks. Absolute found that there are on average 10.6 devices with web proxy/rogue VPN apps per school and 319 unique web proxy/rogue VPN apps in use today, including “Hide My Ass” and “IP Vanish.”  Many of the rogue VPN apps originate in China, and all of them are designed to evade web filtering and other content controls. With an average of 10.6 devices per school harboring web proxies and rogue VPN apps, schools are also at risk of non-compliance with the Children’s Internet Protection Act (CIPA).

  • While 68% of education IT leaders say that cybersecurity is their top priority, 53% rely on client/patch management tools that are proving ineffective in securing their proliferating IT infrastructures. K-12 IT leaders are relying on client/patch management tools to secure the rapidly proliferating number of devices, operating systems, Chrome extensions, educational apps, and unique application versions. Client/patch management agents fail 56% of the time, however, and 9% never recover. There are on average, nine daily encryption agents’ failures, 44% of which never recover. The cybersecurity strategy of relying on native client/patch management isn’t working, leading to funds being wasted on K-12 security controls that don’t scale:

“Wyatt continued, this is not something that can be achieved by simply spending more money… especially when that money comes from public funds. The questions they each need to be asking are if they have the right foundational security measures in place, and whether the controls they have already invested in are working properly. Without key foundational elements of a strong and resilient security approach in place – things like visibility and control, it becomes nearly impossible to protect your students, your data, and your investments.”

  • Providing greater device visibility and endpoint security controls while enabling applications and devices to be more resilient is a solid first step to solving the K-12 cybersecurity crisis. Thwarting the many breach and ransomware attacks K-12 organizations receive every day needs to start by considering every device as part of the network perimeter. Securing K-12 IT networks to the device level delivers asset management and security visibility that native client/patch management tools lack. Having visibility to the device level also gives K-12 IT administrators and educators insights into how they can tailor learning programs for broader adoption. The greater the visibility, the greater the control. K-12 IT administrators can ensure internet safety policies are being adhered to while setting controls to be alerted of suspicious activity or non-compliant devices, including rogue VPNs or stolen devices. Absolute’s Persistence platform provides a persistent connection to each endpoint in a K-12’s one-to-one program, repairing or replacing critical apps that have been disabled or removed.

You can download the full Absolute report here.

Posted in , , , | Tagged , , , , | Leave a response

Three ways to NOT to handle war time pressure in business

By on October 8, 2019

Pressure is a fact of life – especially so in businesses. You cannot eliminate it, but you can probably minimize it with good preparation and training and so on. But whatever you do – you are bound to end up in high pressure situations from time to time. It could be your boss promising more profit to the board or the market changing too fast and all your carefully laid plans going for a toss – there are many reasons why you may end up there.

action adult fast fire
Photo by Pixabay on Pexels.com

The part you have a greater chance to control is how you handle it as a leader. And I think this is where a lot of traditional tactics that we seem to take for granted become counter productive. I want to highlight just three such “common strategies” and why they may not yield the expected results .

Centralized decision making 

The most common tactic when pressure builds is for people higher in the hierarchy to take direct control of execution – especially of what appears as low hanging fruit. You will start seeing memos that go “All travel needs to be approved by the CFO” , “All purchases over $100 need to be approved by the GM” and so on.

On first blush it seems like a real good idea. People will be careful about what they spend money on because no one wants to go to the scary CFO to ask for a $500 air ticket. And multiplied by hundreds of people – that is real cost that is saved.

But what is the reality ? The good sellers will switch to a competitor with less draconian rules. The next best will stay paralyzed thinking they can push their deals when the rules ease off. The CFO would rather spend $500 to get the $100K deal – if only he knew. But this set of people won’t always ask. They will wait. It proceeds along similar lines across all segments. CFO might win the cost battle for a short time and still  lose the larger business war over time.

The accounts payable clerk could have handled this $100 restriction – or automation could have, if the company had the IT skills needed. So on top of killing everyone else’s productivity – the CFO now has a lot more low value work to do. Is that the best use of a highly paid executive’s time ? You cannot manufacture more time for yourself even if you have the most powerful title !

What about the mid level managers who actually lead their teams ? They feel powerless, and for the most part their teams realize it in no time and lose respect for them. So now you have a morale issue and the good managers start floating their CVs in the market too.

A CFO I respect a lot once told me – about a decade or so ago –  “When the business knows what they are doing, my job is to report what they do. When the business does not seem to know what they do – my job is to get it to a shape where I can get back to reporting again”. I think my appreciation for his words have increased every year since then.

Cutting the workforce 

When the going gets hard and saving travel and stationary cost is not enough, leaders have to let go of people. It is a harsh reality of business. Many companies manage cost very effectively on an ongoing basis and even they will occasionally be pushed to cutting head count significantly from time to time.

The traditional wisdom is to cut the bottom rungs first. What gets ignored or forgotten typically is the difference in org structure to handle peace time vs war time. In peace time – you need the matrix and hierarchy to make sure you are investing sufficiently for future. So you will see roles like “Chief of transformation” , “Chief of culture” and so on – and with great conviction, the big bosses will put their best leaders in those roles. That is absolutely the right thing to do as well in that context.

War time is very different. You need your best leaders leading the charge – dealing with the market and your employees directly. If they truly are your best leaders, they cannot be hidden in internal roles managing spreadsheets and on vague ideas.

It is common to hear “all hands on deck” messages from the top at war time. But how many of these peace time roles are actually redeployed to the front line immediately at war time? How many of those senior and expensive people are shown the door if they don’t have the war time skills needed to keep the company alive ? And what saves more money – getting rid of peace time leadership roles at war time , or getting rid of a lot of lower cost less experienced people ? Same question about over lay and ops support roles – matrix requires significant operational overhead. When you are fighting to stay alive, does it really matter much how many ways you can slice and dice your results ?

In my admittedly limited exposure – I have always felt that most leaders are optimists. They think of all troubles in business as temporary – and hence will go away very soon. So why go through the trouble of redeploying etc when there is a less complex way that looks good on a spreadsheet ?

Over communicating 

One of the things that leaders often encourage their teams to do the moment pressure starts mounting is “Please over communicate”. This often happens after most of the critical decision making has already been centralized – thereby reducing the usefulness of the lower level managers . Pleas to over-communicate  is done with great intentions as well –  for example, if people can alert their bosses of important issues early – they can help solve it before it becomes a disaster.

But what really happens when leaders try to over communicate ?

Even when there is no real pressure, communication is not usually a real strength for many business leaders. When they start to over communicate under pressure – the team starts to wonder a few things – “Wow this sounds desperate – should I brush up my CV” , “Clearly you have no respect for my time – and I seriously doubt you understand what my job really is” , “I lost you after the first five minutes – can we get to the point?”, and so on. The reason is simple – the more senior you are, your only way to over communicate is via some “one size fits all” strategy. When people are under pressure – they need clear instructions and specifics, the exact opposite of “one size fits all”.

When the bosses talk in generalities – what are the chances of the lower level employees to go back to them with specific topics ?

So what would be a sensible approach for leaders to handle pressure in their business ?

  1. If you are going to war – declare it explicitly so that all your troops hear it loud and clear .
  2. Define what it takes to win the war. Delegate battles effectively and stay focused on the war.
  3. Act decisively to get rid of the peace-time org structures and redeploy troops for war.
  4. Treat those who are not fit to be warriors with extreme kindness – and try to make it up to them when peace-time returns
  5. Take the lower level leaders into confidence and empower them – centralize strategy as needed without choking information flow, and decentralize execution and communication.
  6. Keep everyone posted as needed – focus on specifics. Resist the urge to over-communicate especially in “one size fits all” fashion.

(Cross-posted @ Vijay's thoughts on all things big and small)

Posted in | Leave a response

What’s New In Gartner’s Hype Cycle For AI, 2019

By on October 7, 2019

What's New In Gartner's Hype Cycle For AI, 2019

  • Between 2018 and 2019, organizations that have deployed artificial intelligence (AI) grew from 4% to 14%, according to Gartner’s 2019 CIO Agenda survey.
  • Conversational AI remains at the top of corporate agendas spurred by the worldwide success of Amazon Alexa, Google Assistant, and others.
  • Enterprises are making progress with AI as it grows more widespread, and they’re also making more mistakes that contribute to their accelerating learning curve.

These and many other new insights are from Gartner Hype Cycle For AI, 2019 published earlier this year and summarized in the recent Gartner blog post, Top Trends on the Gartner Hype Cycle for Artificial Intelligence, 2019.  Gartner’s definition of Hype Cycles includes five phases of a technology’s lifecycle and is explained here. Gartner’s latest Hype Cycle for AI reflects the growing popularity of AutoML, intelligent applications, AI platform as a service or AI cloud services as enterprises ramp up their adoption of AI. The Gartner Hype Cycle for AI, 2019, is shown below:

Details Of What’s New In Gartner’s Hype Cycle For AI, 2019

  • Speech Recognition is less than two years to mainstream adoption and is predicted to deliver the most significant transformational benefits of all technologies on the Hype Cycle. Gartner advises its clients to consider including speech recognition on their short-term AI technology roadmaps. Gartner observes, unlike other technologies within the natural-language processing area, speech to text (and text to speech) is a stand-alone commodity where its modules can be plugged into a variety of natural-language workflows. Leading vendors in this technology area Amazon, Baidu, Cedat 85, Google, IBM, Intelligent Voice, Microsoft, NICE, Nuance, and Speechmatics.
  • Eight new AI-based technologies are included in this year’s Hype Cycle, reflecting Gartner enterprise clients’ plans to scale AI across DevOps and IT while supporting new business models. The latest technologies to be included in the Hype Cycle for AI reflect how enterprises are trying to demystify AI to improve adoption while at the same time, fuel new business models. The new technologies include the following:
  1. AI Cloud Services – AI cloud services are hosted services that allow development teams to incorporate the advantages inherent in AI and machine learning.
  2. AutoML – Automated machine learning (AutoML) is the capability of automating the process of building, deploying, and managing machine learning models.
  3. Augmented Intelligence – Augmented intelligence is a human-centered partnership model of people and artificial intelligence (AI) working together to enhance cognitive performance, including learning, decision making, and new experiences.
  4. Explainable AI – AI researchers define “explainable AI” as an ensemble of methods that make black-box AI algorithms’ outputs sufficiently understandable.
  5. Edge AI – Edge AI refers to the use of AI techniques embedded in IoT endpoints, gateways, and edge devices, in applications ranging from autonomous vehicles to streaming analytics.
  6. Reinforcement Learning – Reinforcement learning has the primary potential for gaming and automation industries and has the potential to lead to significant breakthroughs in robotics, vehicle routing, logistics, and other industrial control scenarios.
  7. Quantum Computing – Quantum computing has the potential to make significant contributions to the areas of systems optimization, machine learning, cryptography, drug discovery, and organic chemistry. Although outside the planning horizon of most enterprises, quantum computing could have strategic impacts in key businesses or operations.
  8. AI Marketplaces – Gartner defines an AI Marketplace as an easily accessible place supported by a technical infrastructure that facilitates the publication, consumption, and billing of reusable algorithms. Some marketplaces are used within an organization to support the internal sharing of prebuilt algorithms among data scientists.
  • Gartner considers the following AI technologies to be on the rise and part of the Innovation Trigger phase of the AI Hype Cycle. AI Marketplaces, Reinforcement Learning, Decision Intelligence, AI Cloud Services, Data Labeling, and Annotation Services, and Knowledge Graphs are now showing signs of potential technology breakthroughs as evidence by early proof-of-concept stories. Technologies in the Innovation Trigger phase of the Hype Cycle often lack usable, scalable products with commercial viability not yet proven.
  • Smart Robots and AutoML are at the peak of the Hype Cycle in 2019. In contrast to the rapid growth of industrial robotics systems that adopted by manufacturers due to the lack of workers, Smart Robots are defined by Gartner as having electromechanical form factors that work autonomously in the physical world, learning in short-term intervals from human-supervised training and demonstrations or by their supervised experiences including taking direction form human voices in a shop floor environment. Whiz robot from SoftBank Robotics is an example of a SmartRobot that will be sold under the robot-as-a service (RaaS) model and originally be available only in Japan. AutoML is one of the most hyped technology in AI this year. Gartner defines automated machine learning (AutoML) as the capability of automating the process of building, deploying, or managing machine learning models. Leading vendors providing AutoML platforms and applications include Amazon SageMaker, Big Squid, dotData, DataRobot, Google Cloud Platform, H2O.ai, KNIME, RapidMiner, and Sky Tree.
  • Nine technologies were removed or reassigned from this years’ Hype Cycle of AI compared to 2018. Gartner has removed nine technologies, often reassigning them into broader categories. Augmented reality and Virtual Reality are now part of augmented intelligence, a more general category, and remains on many other Hype Cycles. Commercial UAVs (drones) are now part of edge AI, a more general category. Ensemble learning had already reached the Plateau in 2018 and has now graduated from the Hype Cycle. Human-in-the-loop crowdsourcing has been replaced by data labeling and annotation services, a broader category. Natural language generation is now included as part of NLP. Knowledge management tools have been replaced by insight engines, which are more relevant to AI. Predictive analytics and prescriptive analytics are now part of decision intelligence, a more general category.

Sources:

Hype Cycle for Artificial Intelligence, 2019, Published 25 July 2019, (Client access reqd.)

Top Trends in the Gartner Hype Cycle for Artificial Intelligence, 2019 published September 12, 2019

Posted in , , , | Tagged , , , , , | Leave a response

Next »