40+ Wearables Companies Growing Their Revenues Worth >USD 70 BN

40+ Wearables Companies Growing Their Revenues Worth >USD 70 BN

40+ WEARABLES COMPANIES GROWING THEIR REVENUES WORTH >USD 70 BN ARE RELYING ON MARKETSANDMARKETS

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Growth Problems Encountered By Wearables Companies-

Customer prioritization and assessing unmet needs:

  • What are the disruptions in our clients’ businesses? How can we support them for our own growth?
  • Who are the most potential customers going forward? Should we prioritize consumer electronics, healthcare, enterprise & industrial applications, or aerospace & defense companies?
  • What are the key unmet needs of customers? Who are the key stakeholders in different settings? Do vendor selection criteria differ by settings? Which new product features should be added to the existing products?

Where to Play:

  • Which applications and technologies should we focus on? Should it be AR/VR, smartwatches, smart bands, or any other?
  • Which regions should we place our bets on? Should we continue with developed countries or do developing countries offer more growth opportunities?

Building a compelling Right to Win (RTW):

  • For M&A, which are the right targets for us? Should we target AR/VR companies or smartwatches, smart bands companies? Should we enter new markets directly or through partners?
  • How can we differentiate from top players? What is their right-to-win vs ours?

Obstacles To Growth For Current Players-

  • Not able to keep pace with fast-evolving wearables industry – New technologies are emerging leading to decreasing cost of devices
  • Many start-ups and emerging companies eating up the market share of established companies
  • Limited clarity on unmet needs, hence requirements for product features
  • Limited clarity on relevant vs redundant wearable devices for the future
  • Unclear picture about the regulatory and reimbursement scenario

WHY DO COMPANIES NEED HELP TO GROW?

Absence Of Original Research :

  • Complex and overlapping markets for library prep and target enrichment kits, hence difficult to calculate market potential and TAM
  • Insufficient secondary research for strategic decisions

Intelligence Is Not Democratised :

  • Client unmet needs need to be understood by all market-facing employees for new product development and vendor selection.
  • Bleak knowledge about upcoming technologies and growing applications such as consumer electronics and healthcare applications

Growth Program Design And Execution :

  • Lack of wearable technology knowledge and practice in competitive intel, pricing and product features, especially in wearables.

SOME UNKNOWNS & ADJACENCIES-

  • Adoption levels of automation in wearables are low. Currently, it ranges between 30-40% globally, however, in developed countries it is approaching 50%. As automation reduces TAT, helps in the minimization of errors, and provides reproducible results, it is largely used in consumer electronics and healthcare applications
  • Increasing focus on personalized health tracking drive the wearables market
  • Markets such as wearables in healthcare, wearables in automotive, and wearables in manufacturing provide immense growth opportunities owing to the rising popularity of IoT and connected devices
  • In target enrichment, developed countries use compact devices are mostly preferred

KEY UNCERTAINTIES/ PERSPECTIVES WHICH INDUSTRY LEADERS SEEK ANSWERS TO:

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Key Questions Of Wearable Companies-

  • Which wearable technology will be relevant and redundant in the next 5 years?
  • Can wearable devices become affordable?
  • How can companies optimize the manufacturing processes to be more agile and efficient to achieve more features which higher efficiency?
  • What regulatory policies can help strategize and achieve higher sales?
  • What can be done to increase the awareness of wearable devices in healthcare applications?

Key Questions Of Companies In Adjacent Markets-

  • What are the regulations surrounding data privacy and security?
  • Which machine learning approaches can be used to address data limitations so that AI models do not lead to misleading insights or faulty predictions?
  • How are companies handling machine bias?
  • When can a 100% AI integration into wearable devices be expected?
  • What will be the impact of automation on the wearables market?

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